A B C D E F G H I J K L M N O P Q R S T U V W

A

Arrays - class marf.util.Arrays.

Extension of java.util.Arrays to allow copying array portions.

Arrays() - Constructor for class marf.util.Arrays

adDataVector - Variable in class marf.Storage.TrainingSample

Array represinting either a feature or mean vector describing the cluster.

adFeatures - Variable in class marf.FeatureExtraction.FeatureExtraction

An array of features extracted (coefficiencies and/or amplitude values)

adMatrix - Variable in class marf.math.Matrix

Matrix itself

adSample - Variable in class marf.Storage.Sample

Sample data array (amplitudes)

add(Matrix, Matrix) - Static method in class marf.math.Matrix

M3 = M1 + M2

addClassificationParam(Object) - Method in class marf.Storage.ModuleParams

Adds (appends) a single classification parameter object

addClassificationParams(Vector) - Method in class marf.Storage.ModuleParams

Adds (appends) classification parameters vector

addFFT(double[]) - Method in class marf.gui.Spectrogram

Adds FFT spectrum to the data to dump

addFeatureExtractionParam(Object) - Method in class marf.Storage.ModuleParams

Adds (appends) a single feature extraction parameter object

addFeatureExtractionParams(Vector) - Method in class marf.Storage.ModuleParams

Adds (appends) feature extraction parameters vector

addFeatureVector(double[], String, int) - Method in class marf.Storage.Cluster

Adds new feature vector to the mean and recomputes the mean

addFeatureVector(double[], int, String, int, int) - Method in class marf.Storage.FeatureSet

Appends yet another feature vector

addFeatureVector(double[], String, int, int, int) - Method in class marf.Storage.TrainingSet

Adds new feature vector to the mean and recomputes the mean

addFilename(String) - Method in class marf.Storage.Cluster

Adds a filename to the training set.

addInput(Neuron, double) - Method in class marf.Classification.NeuralNetwork.Neuron

Adds an input neuron and its associated weight

addLPC(double[], int, int) - Method in class marf.gui.Spectrogram

Adds LPC spectrum to the data to dump

addOutput(Neuron) - Method in class marf.Classification.NeuralNetwork.Neuron

Adds an output neuron

addPreprocessingParam(Object) - Method in class marf.Storage.ModuleParams

Adds (appends) a single preprocessing parameter object

addPreprocessingParams(Vector) - Method in class marf.Storage.ModuleParams

Adds (appends) preprocessing parameters vector

addThread(Thread) - Method in class marf.util.ExpandedThreadGroup

asList(Object[]) - Static method in class marf.util.Arrays

autocorrelation(double[], int) - Static method in class marf.FeatureExtraction.LPC.LPC

Implements the least-square autocorrelation method

B

BANDPASS_FFT_FILTER - Static variable in class marf.MARF

Indicates to use bandpass filter

BandpassFilter - class marf.Preprocessing.FFTFilter.BandpassFilter.

Class BandpassFilter

BandpassFilter(Sample) - Constructor for class marf.Preprocessing.FFTFilter.BandpassFilter

BandpassFilter Constructor

BaseThread - class marf.util.BaseThread.

Class BaseThread Simply one customized base class for many of our own threads.

BaseThread() - Constructor for class marf.util.BaseThread

Default

BaseThread(Runnable) - Constructor for class marf.util.BaseThread

BaseThread(Runnable, String) - Constructor for class marf.util.BaseThread

BaseThread(ThreadGroup, Runnable, String) - Constructor for class marf.util.BaseThread

BaseThread(ThreadGroup, String) - Constructor for class marf.util.BaseThread

Assigns name to the thread and places it to the specified group

BaseThread(ExpandedThreadGroup, String) - Constructor for class marf.util.BaseThread

BaseThread(int) - Constructor for class marf.util.BaseThread

Sets user-specified TID and resets the sequencing from it.

BorderPanel - class marf.gui.util.BorderPanel.

BorderPanel(String) - Constructor for class marf.gui.util.BorderPanel

BorderPanel(String, boolean) - Constructor for class marf.gui.util.BorderPanel

BorderPanel(String, LayoutManager) - Constructor for class marf.gui.util.BorderPanel

BorderPanel(String, LayoutManager, boolean) - Constructor for class marf.gui.util.BorderPanel

ByteUtils - class marf.util.ByteUtils.

Byte conversion utility functions.

ByteUtils() - Constructor for class marf.util.ByteUtils

byteArrayToInt(byte[], boolean) - Static method in class marf.util.ByteUtils

byteArrayToInt(byte[], int, boolean) - Static method in class marf.util.ByteUtils

byteArrayToShort(byte[], boolean) - Static method in class marf.util.ByteUtils

byteArrayToShort(byte[], int, boolean) - Static method in class marf.util.ByteUtils

byteArrayToString(byte[]) - Static method in class marf.util.ByteUtils

byteArrayToString(byte[], int, int) - Static method in class marf.util.ByteUtils

C

CEPSTRAL - Static variable in class marf.MARF

Indicates to use cepstral analysis

CHEBYSHEV_DISTANCE - Static variable in class marf.MARF

Indicates to use Chebyshev distance for classification

CITYBLOCK_DISTANCE - Static variable in class marf.MARF

A synonym to Chebyshev distance

Cepstral - class marf.FeatureExtraction.Cepstral.Cepstral.

Class Cepstral

Cepstral(Preprocessing) - Constructor for class marf.FeatureExtraction.Cepstral.Cepstral

Cepstral Constructor

ChebyshevDistance - class marf.Classification.Distance.ChebyshevDistance.

Class ChebyshevDistance

ChebyshevDistance(FeatureExtraction) - Constructor for class marf.Classification.Distance.ChebyshevDistance

ChebyshevDistance Constructor

Classification - class marf.Classification.Classification.

Class Classification

Classification(FeatureExtraction) - Constructor for class marf.Classification.Classification

Generic Classification Constructor

ClassificationException - exception marf.Classification.ClassificationException.

Class ClassificationException

ClassificationException(String) - Constructor for class marf.Classification.ClassificationException

Generic exception

Cluster - class marf.Storage.Cluster.

Cluster contains a cluster information per subjec.

Cluster() - Constructor for class marf.Storage.Cluster

classify() - Method in class marf.Classification.Classification

Generic classification routine.

classify() - Method in class marf.Classification.Distance.Distance

Classify the feature vector based on whatever distance() derivatives implement.

classify() - Method in class marf.Classification.Markov.Markov

Not Implemented

classify() - Method in class marf.Classification.NeuralNetwork.NeuralNetwork

Neural Network implementation of classification routine

classify() - Method in class marf.Classification.RandomClassification.RandomClassification

Picks an ID at random

classify() - Method in class marf.Classification.Stochastic.Stochastic

Not Implemented

clone() - Method in class marf.math.Matrix

Implements Clonable interface.

commit() - Method in class marf.Classification.NeuralNetwork.NeuralNetwork

Applies changes made to neurons on every net's layer

commit() - Method in class marf.Classification.NeuralNetwork.Neuron

Applies weight changes

copy(double[], int, double[], int, int) - Static method in class marf.util.Arrays

Copies N double elements from source to destination starting at certain index in the destination.

copy(double[], int, double[], int) - Static method in class marf.util.Arrays

Copies N double elements from source to destination starting at certain index in the destination

copy(double[], int, double[]) - Static method in class marf.util.Arrays

Copies source to destination starting at certain index in the destination

copy(double[], double[], int) - Static method in class marf.util.Arrays

Copies N double elements from source to destination

crop(int, int, int, int) - Method in class marf.math.Matrix

cropAudio(double, double) - Method in class marf.Preprocessing.Dummy.Dummy

Dummy implementation of cropAudio() for testing.

cropAudio(double, double) - Method in class marf.Preprocessing.Endpoint.Endpoint

Not Implemented

cropAudio(double, double) - Method in class marf.Preprocessing.FFTFilter.BandpassFilter

Stub implementation of cropAudio()

cropAudio(double, double) - Method in class marf.Preprocessing.FFTFilter.HighFrequencyBoost

Stub implementation of cropAudio()

cropAudio(double, double) - Method in class marf.Preprocessing.FFTFilter.HighPassFilter

Stub implementation of cropAudio()

cropAudio(double, double) - Method in class marf.Preprocessing.FFTFilter.LowPassFilter

Stub implementation of cropAudio()

cropAudio(double, double) - Method in class marf.Preprocessing.Preprocessing

Derivatives implement this method to crop arbitrary part of the audio sample.

cutColumn(int) - Method in class marf.math.Matrix

Shrinks a matrix by removing a specified colum from it.

cutRow(int) - Method in class marf.math.Matrix

D

DEBUG - Static variable in class marf.MARF

Debug flag.

DEFAULT_CHANNELS - Static variable in class marf.Storage.Loaders.WAVLoader

Default 1

DEFAULT_CHUNK_SIZE - Static variable in class marf.FeatureExtraction.FFT.FFT

Default number (1024) of doubles per chunk in the window.

DEFAULT_CHUNK_SIZE - Static variable in class marf.FeatureExtraction.RandomFeatureExtraction.RandomFeatureExtraction

Default number (256) of doubles per chunk in a feature vector.

DEFAULT_COLS - Static variable in class marf.math.Matrix

Default dimension of X of matrix is 4

DEFAULT_EPOCH_NUMBER - Static variable in class marf.Classification.NeuralNetwork.NeuralNetwork

Default number of epoch iterations of 64 if none supplied

DEFAULT_FREQUENCY - Static variable in class marf.Storage.Loaders.WAVLoader

Default 8000 Hz

DEFAULT_FREQUENCY_RESPONSE_SIZE - Static variable in class marf.Preprocessing.FFTFilter.FFTFilter

DEFAULT_MIN_ERROR - Static variable in class marf.Classification.NeuralNetwork.NeuralNetwork

Default minimum training error of 0.1 if none supplied

DEFAULT_OUTPUT_NEURON_BITS - Static variable in class marf.Classification.NeuralNetwork.NeuralNetwork

How many binary Neurons in the output layer.

DEFAULT_ROWS - Static variable in class marf.math.Matrix

Default dimension of Y of matrix is 4

DEFAULT_SAMPLE_BIT_SIZE - Static variable in class marf.Storage.Loaders.WAVLoader

Default 16

DEFAULT_TRAINING_CONSTANT - Static variable in class marf.Classification.NeuralNetwork.NeuralNetwork

Default training constant of 1 if none supplied

DEFAULT_VECTOR_LENGTH - Static variable in class marf.math.Vector

DUMMY - Static variable in class marf.MARF

Indicates to use Dummy preprocessing module (just normalization)

DUMP_BINARY - Static variable in interface marf.Storage.StorageManager

Indicates to dump/restore set data as uncompressed binary file.

DUMP_CSV_TEXT - Static variable in interface marf.Storage.StorageManager

Indicates to dump/restore data as CSV text file.

DUMP_GZIP_BINARY - Static variable in interface marf.Storage.StorageManager

Indicates to dump/restore data as gzipped binary file.

DUMP_XML - Static variable in interface marf.Storage.StorageManager

Indicates to dump/restore data as XML file.

Distance - class marf.Classification.Distance.Distance.

Class Distance

Distance(FeatureExtraction) - Constructor for class marf.Classification.Distance.Distance

Distance Constructor

DoFFT(double[], double[], double[], double[], int) - Static method in class marf.FeatureExtraction.FFT.FFT

FFT algorithm, translated from "Numerical Recipes in C++" Implements the Fast Fourier Transform, which performs a discrete Fourier transform in O(n*log(n)).

DoLPC(double[], double[], double[], int) - Static method in class marf.FeatureExtraction.LPC.LPC

Does LPC algorithm NOTE: input is assumed to be windowed, ie: input.length = N

Dummy - class marf.Preprocessing.Dummy.Dummy.

Class Dummy

Dummy(Sample) - Constructor for class marf.Preprocessing.Dummy.Dummy

Dummy Constructor

data - Variable in class marf.gui.Spectrogram

The data vector

debug(String) - Static method in class marf.MARF

Outputs param to STDERR if DEBUG is enabled

delta - Variable in class marf.Classification.NeuralNetwork.Neuron

Used in error calculation

display() - Method in class marf.math.Matrix

Outputs matrix in text format to STDOUT

distance(double[], double[]) - Method in class marf.Classification.Distance.ChebyshevDistance

ChebyshevDistance implementation

distance(double[], double[]) - Method in class marf.Classification.Distance.Distance

Generic distance routine.

distance(double[], double[]) - Method in class marf.Classification.Distance.EuclideanDistance

EuclideanDistance implementation

distance(double[], double[]) - Method in class marf.Classification.Distance.MahalanobisDistance

Partial MahalanobisDistance implementation

distance(double[], double[]) - Method in class marf.Classification.Distance.MinkowskiDistance

MinkowskiDistance implementation

divide(Matrix, double) - Static method in class marf.math.Matrix

M / d

dump() - Method in class marf.Classification.Classification

Generic implementation of dump() for TrainingSet

dump() - Method in class marf.Classification.Markov.Markov

Not Implemented

dump() - Method in class marf.Classification.NeuralNetwork.NeuralNetwork

Dumps Neural Net to an XML file

dump() - Method in class marf.Classification.RandomClassification.RandomClassification

Dumps "training set" of IDs

dump() - Method in class marf.Classification.Stochastic.Stochastic

Not Implemented

dump() - Method in class marf.FeatureExtraction.Cepstral.Cepstral

Not Implemented

dump() - Method in class marf.FeatureExtraction.F0.F0

Not Implemented

dump() - Method in class marf.FeatureExtraction.FFT.FFT

Not Implemented

dump() - Method in class marf.FeatureExtraction.LPC.LPC

Not Implemented

dump() - Method in class marf.FeatureExtraction.RandomFeatureExtraction.RandomFeatureExtraction

Not Implemented

dump() - Method in class marf.FeatureExtraction.Segmentation.Segmentation

Not Implemented

dump() - Method in class marf.Preprocessing.Dummy.Dummy

Dummy implementation of dump() for testing.

dump() - Method in class marf.Preprocessing.Endpoint.Endpoint

Not Implemented

dump() - Method in class marf.Preprocessing.Preprocessing

Not Implemented

dump() - Method in interface marf.Storage.StorageManager

An object must know how dump itself to a file.

dump() - Method in class marf.Storage.TrainingSet

Dump the current training set to disk

dump() - Method in class marf.gui.Spectrogram

Dumps spectrogram

dump() - Method in class marf.gui.WaveGrapher

Dumps graph of wave in the CSV format

dumpCSV(BufferedWriter) - Method in class marf.Storage.TrainingSample

Write one training sample to a text file.

dumpXML(String) - Method in class marf.Classification.NeuralNetwork.NeuralNetwork

Dumps Neural Network as XML file

E

EAST - Static variable in class marf.math.Matrix.Direction

ENDPOINT - Static variable in class marf.MARF

Indicates to use endpointing

EUCLIDEAN_DISTANCE - Static variable in class marf.MARF

Indicates to use Euclidean distance for classification

Endpoint - class marf.Preprocessing.Endpoint.Endpoint.

Class Endpoint

Endpoint(Sample) - Constructor for class marf.Preprocessing.Endpoint.Endpoint

Endpoint Constructor

EuclideanDistance - class marf.Classification.Distance.EuclideanDistance.

Class EuclideanDistance

EuclideanDistance(FeatureExtraction) - Constructor for class marf.Classification.Distance.EuclideanDistance

EuclideanDistance Constructor

ExpandedThreadGroup - class marf.util.ExpandedThreadGroup.

Provides some useful extensions to java.lang.ThreadGroup one would normally expect to be in a "group".

ExpandedThreadGroup(String) - Constructor for class marf.util.ExpandedThreadGroup

Mimic parent's constructor.

ExpandedThreadGroup(ExpandedThreadGroup, String) - Constructor for class marf.util.ExpandedThreadGroup

Mimic parent's constructor.

enumerate(boolean) - Method in class marf.util.ExpandedThreadGroup

Another enumeration, that allocates a new array and populates it with currently active threads with ThreadGroup's enumerate().

equals(Matrix) - Method in class marf.math.Matrix

this == M

equals(Matrix, Matrix) - Static method in class marf.math.Matrix

M1 == M2

equals(boolean[], boolean[]) - Static method in class marf.util.Arrays

equals(byte[], byte[]) - Static method in class marf.util.Arrays

equals(char[], char[]) - Static method in class marf.util.Arrays

equals(double[], double[]) - Static method in class marf.util.Arrays

equals(float[], float[]) - Static method in class marf.util.Arrays

equals(int[], int[]) - Static method in class marf.util.Arrays

equals(long[], long[]) - Static method in class marf.util.Arrays

equals(Object[], Object[]) - Static method in class marf.util.Arrays

equals(short[], short[]) - Static method in class marf.util.Arrays

eval() - Method in class marf.Classification.NeuralNetwork.Neuron

Evaluates current neuron's value

exhaustMatrix() - Method in class marf.math.Matrix

"Destroys" the internal array matrix by setting it to null.

existsFilename(String) - Method in class marf.Storage.Cluster

Check existance of the file in the training set.

extend(Matrix) - Method in class marf.math.Matrix

extend(Matrix, Matrix.Direction) - Method in class marf.math.Matrix

extractFeatures() - Method in class marf.FeatureExtraction.Cepstral.Cepstral

Not Implemented

extractFeatures() - Method in class marf.FeatureExtraction.F0.F0

Not Implemented

extractFeatures() - Method in class marf.FeatureExtraction.FFT.FFT

FFT Implementation of extractFeatures()

extractFeatures() - Method in class marf.FeatureExtraction.FeatureExtraction

Abstract feature extraction routine.

extractFeatures() - Method in class marf.FeatureExtraction.LPC.LPC

LPC Implementation of extractFeatures()

extractFeatures() - Method in class marf.FeatureExtraction.RandomFeatureExtraction.RandomFeatureExtraction

Random Gaussian feature extracton.

extractFeatures() - Method in class marf.FeatureExtraction.Segmentation.Segmentation

Not Implemented

F

F0 - class marf.FeatureExtraction.F0.F0.

Class F0

F0(Preprocessing) - Constructor for class marf.FeatureExtraction.F0.F0

F0 Constructor

F0 - Static variable in class marf.MARF

Indicates to use F0

FFT - class marf.FeatureExtraction.FFT.FFT.

Class FFT

FFT(Preprocessing) - Constructor for class marf.FeatureExtraction.FFT.FFT

FFT Constructor

FFT - Static variable in class marf.MARF

Indicates to use FFT

FFTFilter - class marf.Preprocessing.FFTFilter.FFTFilter.

FFTFilter class

FFTFilter(Sample) - Constructor for class marf.Preprocessing.FFTFilter.FFTFilter

FFTFilter Constructor

FeatureExtraction - class marf.FeatureExtraction.FeatureExtraction.

Class FeatureExtraction

FeatureExtraction(Preprocessing) - Constructor for class marf.FeatureExtraction.FeatureExtraction

FeatureExtraction constructor

FeatureExtractionException - exception marf.FeatureExtraction.FeatureExtractionException.

Class FeatureExtractionException

FeatureExtractionException(String) - Constructor for class marf.FeatureExtraction.FeatureExtractionException

Generic exception

FeatureSet - class marf.Storage.FeatureSet.

FeatureSet -- Encapsulates Subject ID and subject's "feature" sets

FeatureSet() - Constructor for class marf.Storage.FeatureSet

Construct a training set object.

fill(boolean[], boolean) - Static method in class marf.util.Arrays

fill(boolean[], int, int, boolean) - Static method in class marf.util.Arrays

fill(byte[], byte) - Static method in class marf.util.Arrays

fill(byte[], int, int, byte) - Static method in class marf.util.Arrays

fill(char[], char) - Static method in class marf.util.Arrays

fill(char[], int, int, char) - Static method in class marf.util.Arrays

fill(double[], double) - Static method in class marf.util.Arrays

fill(double[], int, int, double) - Static method in class marf.util.Arrays

fill(float[], float) - Static method in class marf.util.Arrays

fill(float[], int, int, float) - Static method in class marf.util.Arrays

fill(int[], int) - Static method in class marf.util.Arrays

fill(int[], int, int, int) - Static method in class marf.util.Arrays

fill(long[], int, int, long) - Static method in class marf.util.Arrays

fill(long[], long) - Static method in class marf.util.Arrays

fill(Object[], int, int, Object) - Static method in class marf.util.Arrays

fill(Object[], Object) - Static method in class marf.util.Arrays

fill(short[], int, int, short) - Static method in class marf.util.Arrays

fill(short[], short) - Static method in class marf.util.Arrays

filter(double[], double[]) - Method in class marf.Preprocessing.FFTFilter.FFTFilter

Perform a filter by the following algorithm: sample -> window -> FFT -> buffer buffer * frequency response buffer -> IFFT -> window -> sample Window used is square root of Hamming window, because the sum at half-window overlap is a constant, which avoids amplitude distortion from noise.

freqResponse - Variable in class marf.Preprocessing.FFTFilter.FFTFilter

Frequency repsonse to be multiplied by the incoming value

G

generate(int, int[], int) - Method in class marf.Classification.NeuralNetwork.NeuralNetwork

Generates virgin net at random.

getAudioFormat() - Method in class marf.Storage.Sample

getClassification() - Static method in class marf.MARF

Retrieves current Classification reference

getClassificationMethod() - Static method in class marf.MARF

Gets classification method to be used

getClassificationParams() - Method in class marf.Storage.ModuleParams

getClusters() - Method in class marf.Storage.TrainingSet

Retrieves training samples

getCols() - Method in class marf.math.Matrix

getConfig() - Static method in class marf.MARF

Returns a string representation of the current MARF configuration

getCrossProduct(Vector, Vector) - Method in class marf.math.Vector

getCurrentSubject() - Static method in class marf.MARF

Gets ID of a subject currently being trained on

getDataVector() - Method in class marf.Storage.TrainingSample

Retrieves the data vector

getDeterminant() - Method in class marf.math.Matrix

Calculates determinant of this matrix

getDirection() - Method in class marf.math.Matrix.Direction

getDotProduct(Vector, Vector) - Method in class marf.math.Vector

getDumpMode() - Method in class marf.Storage.TrainingSet

Retrieves current dump mode

getDumpSpectrogram() - Static method in class marf.MARF

Whether spectrogram wanted or not

getDumpWaveGraph() - Static method in class marf.MARF

Whether wave graph wanted or not

getElement(int, int) - Method in class marf.math.Matrix

getElement(int) - Method in class marf.math.Vector

getElements() - Method in class marf.math.Matrix

Returns number of the elements of the matrix.

getFeatureExtraction() - Static method in class marf.MARF

Retrieves current FeatureExtraction reference

getFeatureExtractionMethod() - Static method in class marf.MARF

Gets currently selected feature extraction method.

getFeatureExtractionMethod() - Method in class marf.Storage.TrainingSet

Returns preprocessing method used on this training set

getFeatureExtractionParams() - Method in class marf.Storage.ModuleParams

getFeatureVectors() - Method in class marf.Storage.FeatureSet

Retrieves training samples

getFeaturesArray() - Method in class marf.FeatureExtraction.FeatureExtraction

Allows retrieval of a feature vector

getID() - Method in class marf.Storage.Result

Returns result's ID

getInnerProduct(Vector, Vector) - Method in class marf.math.Vector

getIntVersion() - Static method in class marf.MARF

Returns an integer representation of the MARF version

getLength() - Method in class marf.math.Vector

getMatrix2D() - Method in class marf.math.Matrix

Returns internal matrix representation as 2-dimensional array of doubles

getMatrixArray() - Method in class marf.math.Matrix

getMeanCount() - Method in class marf.Storage.Cluster

Retrieves current mean count

getMeanVector() - Method in class marf.Storage.Cluster

Retrieves the mean vector

getMessage() - Method in class marf.util.MARFException

Returns string representation of the error message.

getModuleParams() - Static method in class marf.MARF

Gets module-specific parameters an application programmer passed on to the module

getNextChunk(double[]) - Method in class marf.Storage.Sample

Gets the next chunk of audio data and places it into chunkArray.

getNextTID() - Static method in class marf.util.BaseThread

Lets to examine the next TID to be assigned.

getPreprocessing() - Static method in class marf.MARF

Retrieves current Preprocessing reference

getPreprocessingMethod() - Static method in class marf.MARF

Gets currently selected preprocessing method.

getPreprocessingMethod() - Method in class marf.Storage.TrainingSet

Returns preprocessing method used on this training set

getPreprocessingParams() - Method in class marf.Storage.ModuleParams

getRes() - Method in class marf.Classification.NeuralNetwork.NeuralNetwork

Gets outputs of a neural network run

getResult() - Method in class marf.Classification.Classification

Retrieves the classification result

getResult() - Static method in class marf.MARF

Gets the entire Result object

getRows() - Method in class marf.math.Matrix

getSample() - Static method in class marf.MARF

Retrieves current Sample reference

getSample() - Method in class marf.Preprocessing.Preprocessing

Returns enclosed sample.

getSample() - Method in class marf.Storage.SampleLoader

getSampleArray() - Method in class marf.Storage.Sample

Retrieves array containing audio data of the entire sample.

getSampleFile() - Static method in class marf.MARF

Obtains filename of a sample currently being processed

getSampleFormat() - Static method in class marf.MARF

Gets input sample file format

getSampleLoader() - Static method in class marf.MARF

Retrieves current SampleLoader reference

getSampleSize() - Method in class marf.Storage.Sample

Returns the length of the sample.

getSampleSize() - Method in class marf.Storage.SampleLoader

Retrieves the length of the sample (# of audio data in the audio stream).

getSecondClosestID() - Method in class marf.Storage.Result

Returns second closest ID

getSubjectID() - Method in class marf.Storage.TrainingSample

Retrieves Subject ID of a particular training sample

getTID() - Method in class marf.util.BaseThread

Retrieves our TID

getTrainingSetFile() - Method in class marf.Storage.TrainingSet

Retrieves current training set file name

getUnitVector() - Method in class marf.math.Vector

getVersion() - Static method in class marf.MARF

Returns a string representation of the MARF version

H

HIDDEN - Static variable in class marf.Classification.NeuralNetwork.Neuron

Indicates middle (hidden) neuron

HIGH_FREQUENCY_BOOST_FFT_FILTER - Static variable in class marf.MARF

Indicates to use filter boosting high frequencies

HIGH_PASS_FFT_FILTER - Static variable in class marf.MARF

Indicates to use high pass FFT filter

HighFrequencyBoost - class marf.Preprocessing.FFTFilter.HighFrequencyBoost.

HighFrequencyBoost Class

HighFrequencyBoost(Sample) - Constructor for class marf.Preprocessing.FFTFilter.HighFrequencyBoost

HighFrequencyBoost Constructor

HighPassFilter - class marf.Preprocessing.FFTFilter.HighPassFilter.

HighPassFilter Class

HighPassFilter(Sample) - Constructor for class marf.Preprocessing.FFTFilter.HighPassFilter

HighPassFilter Constructor

hamming(int, int) - Static method in class marf.FeatureExtraction.FeatureExtraction

Retrieves a single value of hamming window based on length and index within the widow

hamming(double[]) - Static method in class marf.FeatureExtraction.FeatureExtraction

Applies hamming window to an array of doubles

I

INPUT - Static variable in class marf.Classification.NeuralNetwork.Neuron

Indicates input neuron

InvalidSampleFormatException - exception marf.util.InvalidSampleFormatException.

Class InvalidSampleFormatException

InvalidSampleFormatException(int) - Constructor for class marf.util.InvalidSampleFormatException

Exception for specific sample format

InvalidSampleFormatException(String) - Constructor for class marf.util.InvalidSampleFormatException

Generic exception

i() - Method in class marf.math.Vector

iArrayIndex - Variable in class marf.Storage.Sample

Chunk pointer in the sample array

iCols - Variable in class marf.math.Matrix

Actual number of columns in the matrix.

iFormat - Variable in class marf.Storage.Sample

Sample's format

iRows - Variable in class marf.math.Matrix

Actual number of rows in the matrix.

iSubjectID - Variable in class marf.Storage.TrainingSample

Which subject this feature vector is associated with.

iTID - Variable in class marf.util.BaseThread

Our Thread ID

incMeanCount() - Method in class marf.Storage.Cluster

Increases mean count by one

indent(BufferedWriter, int) - Static method in class marf.Classification.NeuralNetwork.NeuralNetwork

Indents the output according to the requested tabulation.

initialize(String, boolean) - Method in class marf.Classification.NeuralNetwork.NeuralNetwork

Parses XML and produces NNet.

inverse() - Method in class marf.math.Matrix

Matrix inversion

isIdentity() - Method in class marf.math.Matrix

Checks for strict identity matrix.

isNearlyIdentity(double) - Method in class marf.math.Matrix

isNearlyIdentity() - Method in class marf.math.Matrix

isOrthogonal(Vector) - Method in class marf.math.Vector

isReduced() - Method in class marf.math.Matrix

J

JAXP_SCHEMA_LANGUAGE - Static variable in class marf.Classification.NeuralNetwork.NeuralNetwork

JAXP 1.2 Schema

JAXP_SCHEMA_SOURCE - Static variable in class marf.Classification.NeuralNetwork.NeuralNetwork

JAXP 1.2 Schem URL

j() - Method in class marf.math.Vector

join() - Method in class marf.util.ExpandedThreadGroup

Wait for all the threads in the group to terminate.

K

k() - Method in class marf.math.Vector

L

LOW_PASS_FFT_FILTER - Static variable in class marf.MARF

Indicates to use low pass FFT filter

LPC - class marf.FeatureExtraction.LPC.LPC.

Class LPC

LPC(Preprocessing) - Constructor for class marf.FeatureExtraction.LPC.LPC

LPC Constructor

LPC - Static variable in class marf.MARF

Indicates to use LPC

LowPassFilter - class marf.Preprocessing.FFTFilter.LowPassFilter.

LowPassFilter Class

LowPassFilter(Sample) - Constructor for class marf.Preprocessing.FFTFilter.LowPassFilter

LowPassFilter Constructor

loadRow(int, Vector) - Method in class marf.math.Matrix

loadSample(File) - Method in class marf.Storage.Loaders.MP3Loader

Not Implemented

loadSample(File) - Method in class marf.Storage.Loaders.ULAWLoader

Not Implemented

loadSample(File) - Method in class marf.Storage.Loaders.WAVLoader

Loads WAV sample data from a file.

loadSample(File) - Method in class marf.Storage.SampleLoader

SampleLoader interface.

loadSample(String) - Method in class marf.Storage.SampleLoader

Same as loadSample(File) but takes filename as an argument.

M

MAHALANOBIS_DISTANCE - Static variable in class marf.MARF

Indicates to use Mahalanobis distance for classification

MANHATTAN_DISTANCE - Static variable in class marf.MARF

A synonym to Chebyshev distance

MARF - class marf.MARF.

Class MARF

MARFException - exception marf.util.MARFException.

Class MARFException

MARFException(String) - Constructor for class marf.util.MARFException

Generic exception

MARFException(String, Exception) - Constructor for class marf.util.MARFException

This is used for debug purposes only with some unusual Exception's.

MARKOV - Static variable in class marf.MARF

Indicates to use Hidden Markov Models for classification

MINKOWSKI_DISTANCE - Static variable in class marf.MARF

Indicates to use Minkowski distance for classification

MP3 - Static variable in class marf.MARF

Indicates MP3 incoming sample file format

MP3 - Static variable in class marf.Storage.Sample

MP3 sample format

MP3Loader - class marf.Storage.Loaders.MP3Loader.

Not Implemented

MP3Loader() - Constructor for class marf.Storage.Loaders.MP3Loader

MP3 Loader Constructor

MahalanobisDistance - class marf.Classification.Distance.MahalanobisDistance.

Class MahalanobisDistance

MahalanobisDistance(FeatureExtraction) - Constructor for class marf.Classification.Distance.MahalanobisDistance

MahalanobisDistance Constructor

Markov - class marf.Classification.Markov.Markov.

Class Markov

Markov(FeatureExtraction) - Constructor for class marf.Classification.Markov.Markov

Markov Constructor

Matrix - class marf.math.Matrix.

Algebraic operations on matrices.

Matrix() - Constructor for class marf.math.Matrix

Default constructor.

Matrix(int, int) - Constructor for class marf.math.Matrix

Constructor with custom dimensions.

Matrix(int, int, double) - Constructor for class marf.math.Matrix

Constructor with custom dimensions and initial fill value.

Matrix(Matrix) - Constructor for class marf.math.Matrix

A-la copy-constructor

Matrix(double[]) - Constructor for class marf.math.Matrix

This constructor makes up a vector.

Matrix(double[], boolean) - Constructor for class marf.math.Matrix

This constructor makes up a transposed vector.

Matrix(double[][]) - Constructor for class marf.math.Matrix

Constructs a 2D matrix from a 2D array.

Matrix.Direction - class marf.math.Matrix.Direction.

Indicates the direction in which a matrix to be extended.

Matrix.Direction() - Constructor for class marf.math.Matrix.Direction

Default constructor.

Matrix.Direction(int) - Constructor for class marf.math.Matrix.Direction

Constructor.

Matrix.Direction(Matrix.Direction) - Constructor for class marf.math.Matrix.Direction

Copy Constructor

MinkowskiDistance - class marf.Classification.Distance.MinkowskiDistance.

Class MinkowskiDistance

MinkowskiDistance(FeatureExtraction) - Constructor for class marf.Classification.Distance.MinkowskiDistance

MinkowskiDistance Constructor

ModuleParams - class marf.Storage.ModuleParams.

Class ModuleParams

ModuleParams() - Constructor for class marf.Storage.ModuleParams

Default Constructor

main(String[]) - Static method in class test

makeIdentity() - Method in class marf.math.Matrix

Makes current matrix an identity one

marf - package marf

marf.Classification - package marf.Classification

marf.Classification.Distance - package marf.Classification.Distance

marf.Classification.Markov - package marf.Classification.Markov

marf.Classification.NeuralNetwork - package marf.Classification.NeuralNetwork

marf.Classification.RandomClassification - package marf.Classification.RandomClassification

marf.Classification.Stochastic - package marf.Classification.Stochastic

marf.FeatureExtraction - package marf.FeatureExtraction

marf.FeatureExtraction.Cepstral - package marf.FeatureExtraction.Cepstral

marf.FeatureExtraction.F0 - package marf.FeatureExtraction.F0

marf.FeatureExtraction.FFT - package marf.FeatureExtraction.FFT

marf.FeatureExtraction.LPC - package marf.FeatureExtraction.LPC

marf.FeatureExtraction.RandomFeatureExtraction - package marf.FeatureExtraction.RandomFeatureExtraction

marf.FeatureExtraction.Segmentation - package marf.FeatureExtraction.Segmentation

marf.Preprocessing - package marf.Preprocessing

marf.Preprocessing.Dummy - package marf.Preprocessing.Dummy

marf.Preprocessing.Endpoint - package marf.Preprocessing.Endpoint

marf.Preprocessing.FFTFilter - package marf.Preprocessing.FFTFilter

marf.Stats - package marf.Stats

marf.Storage - package marf.Storage

marf.Storage.Loaders - package marf.Storage.Loaders

marf.gui - package marf.gui

marf.gui.util - package marf.gui.util

marf.math - package marf.math

marf.util - package marf.util

max - Variable in class marf.gui.Spectrogram

Current maximum

min - Variable in class marf.gui.Spectrogram

Current minimum

minus(Matrix, Matrix) - Static method in class marf.math.Matrix

M3 = M1 - M2

minus(Matrix) - Method in class marf.math.Matrix

this - M

minusUnary(Matrix) - Static method in class marf.math.Matrix

M = -M

multiply(Matrix) - Method in class marf.math.Matrix

M1 = this * M

multiply(Matrix, Matrix) - Static method in class marf.math.Matrix

M3 = M1 * M2

multiply(Matrix, double) - Static method in class marf.math.Matrix

M = M * d

multiply(double) - Method in class marf.math.Matrix

this = this * d

multiply(double, Matrix) - Static method in class marf.math.Matrix

M1 = d * M

N

NEURAL_NETWORK - Static variable in class marf.MARF

Indicates to use Neural Network for classification

NORTH - Static variable in class marf.math.Matrix.Direction

NeuralNetwork - class marf.Classification.NeuralNetwork.NeuralNetwork.

Class NeuralNetwork

NeuralNetwork(FeatureExtraction) - Constructor for class marf.Classification.NeuralNetwork.NeuralNetwork

NeuralNetwork Constructor

Neuron - class marf.Classification.NeuralNetwork.Neuron.

Class Neuron

Neuron(String, int) - Constructor for class marf.Classification.NeuralNetwork.Neuron

Neuron Constructor

NormalFFT(double[], double[], double[]) - Static method in class marf.FeatureExtraction.FFT.FFT

Performs a normal FFT, taking a real input (supposedly an audio sample) and returns the frequency analysis in terms of "magnitude" and "phase angle".

NormalFFT(double[], double[]) - Static method in class marf.FeatureExtraction.FFT.FFT

Performs a normal FFT, taking a real input (supposedly an audio sample) and returns the frequency analysis in terms of "magnitude".

NotImplementedException - exception marf.util.NotImplementedException.

Class NotImplementedException

NotImplementedException(String) - Constructor for class marf.util.NotImplementedException

Generic exception

name - Variable in class marf.Classification.NeuralNetwork.Neuron

Neuron's name

normalize() - Method in class marf.Preprocessing.Preprocessing

Normalization of incoming samples by amplitude.

normalize() - Method in class marf.math.Vector

O

OUTPUT - Static variable in class marf.Classification.NeuralNetwork.Neuron

Indicates output neuron

oAudioFormat - Variable in class marf.Storage.SampleLoader

Properties of a wave.

oAudioInputStream - Variable in class marf.Storage.SampleLoader

Stream representing wave sample.

oByteArrayOutputStream - Variable in class marf.Storage.SampleLoader

Output stream used for writing audio data.

oFeatureExtraction - Variable in class marf.Classification.Classification

Reference to the FeatureExtraction object

oFilenames - Variable in class marf.Storage.TrainingSample

A list of filenames that were used in training for this cluster.

oGroup - Variable in class marf.util.ExpandedThreadGroup

oPreprocessing - Variable in class marf.FeatureExtraction.FeatureExtraction

Internal reference to the Preprocessing module

oResult - Variable in class marf.Classification.Classification

Classification Result

oSample - Variable in class marf.Preprocessing.Preprocessing

Sample container

oSample - Variable in class marf.Storage.SampleLoader

Sample references of the sample to be loaded.

oTrainingSet - Variable in class marf.Classification.Classification

TrainingSet Container

outputEncoding - Static variable in class marf.Classification.NeuralNetwork.NeuralNetwork

All output will use this encoding

P

Preprocessing - class marf.Preprocessing.Preprocessing.

Class Preprocessing

Preprocessing(Sample) - Constructor for class marf.Preprocessing.Preprocessing

Preprocessing Constructor

PreprocessingException - exception marf.Preprocessing.PreprocessingException.

Class PreprocessingException

PreprocessingException(String) - Constructor for class marf.Preprocessing.PreprocessingException

Preprocessing exception

preprocess() - Method in class marf.Preprocessing.Dummy.Dummy

Dummy implementation of preprocess() for testing.

preprocess() - Method in class marf.Preprocessing.Endpoint.Endpoint

Not Implemented

preprocess() - Method in class marf.Preprocessing.FFTFilter.FFTFilter

FFTFilter implementation of preprocess()

preprocess() - Method in class marf.Preprocessing.FFTFilter.HighFrequencyBoost

Overrides FFTFilter's preprocess with extra normalization after boost.

preprocess() - Method in class marf.Preprocessing.Preprocessing

Derivatives implement this method to do general preprocessing and perhaps calling removeNoise() and removeSilence().

printXML(BufferedWriter, int) - Method in class marf.Classification.NeuralNetwork.Neuron

Dumps XML of the current Neuron

Q

queryResultID() - Static method in class marf.MARF

Queries for the final classification result

R

RANDOM_CLASSIFICATION - Static variable in class marf.MARF

Indicates to use random classification

RANDOM_FEATURE_EXTRACTION - Static variable in class marf.MARF

Indicates to use random feature extraction

RandomClassification - class marf.Classification.RandomClassification.RandomClassification.

Class RandomClassification

RandomClassification(FeatureExtraction) - Constructor for class marf.Classification.RandomClassification.RandomClassification

RandomClassification Constructor

RandomFeatureExtraction - class marf.FeatureExtraction.RandomFeatureExtraction.RandomFeatureExtraction.

Class RandomFeatureExtraction.

RandomFeatureExtraction(Preprocessing) - Constructor for class marf.FeatureExtraction.RandomFeatureExtraction.RandomFeatureExtraction

RandomFeatureExtraction Constructor

Result - class marf.Storage.Result.

Class Result

Result() - Constructor for class marf.Storage.Result

Default Constructor Equivalent to Result(0)

Result(int) - Constructor for class marf.Storage.Result

ID Constructor

Result(double[]) - Constructor for class marf.Storage.Result

ResultSet Constructor Equivalent to Result(0, padResultSet)

Result(int, double[]) - Constructor for class marf.Storage.Result

ID ResultSet Constructor

Result(int, Vector) - Constructor for class marf.Storage.Result

ID Vector ResultSet Constructor

readAudioData(double[]) - Method in class marf.Storage.Loaders.MP3Loader

Not Implemented

readAudioData(double[]) - Method in class marf.Storage.Loaders.ULAWLoader

Not Implemented

readAudioData(double[]) - Method in class marf.Storage.Loaders.WAVLoader

Buffers out the contents of audioBuffer into audioData

readAudioData(double[]) - Method in class marf.Storage.SampleLoader

Reads audio data from the sample's audio stream into paiAudioData.

recognize() - Static method in class marf.MARF

Recognition/Identification mode

removeNoise() - Method in class marf.Preprocessing.Dummy.Dummy

Dummy implementation of removeNoise() for testing.

removeNoise() - Method in class marf.Preprocessing.Endpoint.Endpoint

Not Implemented

removeNoise() - Method in class marf.Preprocessing.FFTFilter.BandpassFilter

Stub implementation of removeNoise()

removeNoise() - Method in class marf.Preprocessing.FFTFilter.HighFrequencyBoost

Stub implementation of removeNoise()

removeNoise() - Method in class marf.Preprocessing.FFTFilter.HighPassFilter

Stub implementation of removeNoise()

removeNoise() - Method in class marf.Preprocessing.FFTFilter.LowPassFilter

Stub implementation of removeNoise()

removeNoise() - Method in class marf.Preprocessing.Preprocessing

Derivatives implement this method to remove noise from the sample.

removeSilence() - Method in class marf.Preprocessing.Dummy.Dummy

Dummy implementation of removeSilence() for testing.

removeSilence() - Method in class marf.Preprocessing.Endpoint.Endpoint

Not Implemented

removeSilence() - Method in class marf.Preprocessing.FFTFilter.BandpassFilter

Stub implementation of removeSilence()

removeSilence() - Method in class marf.Preprocessing.FFTFilter.HighFrequencyBoost

Stub implementation of removeSilence()

removeSilence() - Method in class marf.Preprocessing.FFTFilter.HighPassFilter

Stub implementation of removeSilence()

removeSilence() - Method in class marf.Preprocessing.FFTFilter.LowPassFilter

Stub implementation of removeSilence()

removeSilence() - Method in class marf.Preprocessing.Preprocessing

Derivatives implement this method to remove silence.

reset() - Method in class marf.Storage.SampleLoader

Resets the marker for the audio stream.

resetArrayMark() - Method in class marf.Storage.Sample

Resets the marker used for reading audio data from sample array

restore() - Method in class marf.Classification.Classification

Generic implementation of restore() for TrainingSet

restore() - Method in class marf.Classification.Markov.Markov

Not Implemented

restore() - Method in class marf.Classification.NeuralNetwork.NeuralNetwork

Restores Neural Net from an XML file

restore() - Method in class marf.Classification.RandomClassification.RandomClassification

Restores "training set" of IDs

restore() - Method in class marf.Classification.Stochastic.Stochastic

Not Implemented

restore() - Method in class marf.FeatureExtraction.Cepstral.Cepstral

Not Implemented

restore() - Method in class marf.FeatureExtraction.F0.F0

Not Implemented

restore() - Method in class marf.FeatureExtraction.FFT.FFT

Not Implemented

restore() - Method in class marf.FeatureExtraction.LPC.LPC

Not Implemented

restore() - Method in class marf.FeatureExtraction.RandomFeatureExtraction.RandomFeatureExtraction

Not Implemented

restore() - Method in class marf.FeatureExtraction.Segmentation.Segmentation

Not Implemented

restore() - Method in class marf.Preprocessing.Dummy.Dummy

Dummy implementation of restore() for testing.

restore() - Method in class marf.Preprocessing.Endpoint.Endpoint

Not Implemented

restore() - Method in class marf.Preprocessing.Preprocessing

Not Implemented

restore() - Method in interface marf.Storage.StorageManager

An object must know how retore its non-transient data structures from a file.

restore() - Method in class marf.Storage.TrainingSet

Retrieve the current training set from disk

restore() - Method in class marf.gui.Spectrogram

Not implemented

restore() - Method in class marf.gui.WaveGrapher

Not implemented

restoreCSV(BufferedReader) - Method in class marf.Storage.TrainingSample

Retrieve one training sample from a text file.

result - Variable in class marf.Classification.NeuralNetwork.Neuron

Current Neuron's result

rowOperation(double, int) - Method in class marf.math.Matrix

rowOperation(double, int, char, double, int) - Method in class marf.math.Matrix

rowReduce() - Method in class marf.math.Matrix

S

SEGMENTATION - Static variable in class marf.MARF

Indicates to use segmentation

SOUTH - Static variable in class marf.math.Matrix.Direction

STOCHASTIC - Static variable in class marf.MARF

Indicates to use stochastic models for classification

Sample - class marf.Storage.Sample.

Class Sample

Sample() - Constructor for class marf.Storage.Sample

Default constructor

Sample(double[]) - Constructor for class marf.Storage.Sample

Accepts pre-set sample for testing

Sample(int) - Constructor for class marf.Storage.Sample

Constructor with format indication

SampleLoader - class marf.Storage.SampleLoader.

Absract Class SampleLoader

SampleLoader() - Constructor for class marf.Storage.SampleLoader

Default constructor.

Segmentation - class marf.FeatureExtraction.Segmentation.Segmentation.

Class Segmentation

Segmentation(Preprocessing) - Constructor for class marf.FeatureExtraction.Segmentation.Segmentation

Segmentation Constructor

Spectrogram - class marf.gui.Spectrogram.

Class Spectrogram

Spectrogram() - Constructor for class marf.gui.Spectrogram

Constructor

Spectrogram(String) - Constructor for class marf.gui.Spectrogram

Constructor with a feature extraction method name

StatsCollector - class marf.Stats.StatsCollector.

Not Implemented

StatsCollector() - Constructor for class marf.Stats.StatsCollector

Stochastic - class marf.Classification.Stochastic.Stochastic.

Class Stochastic

Stochastic(FeatureExtraction) - Constructor for class marf.Classification.Stochastic.Stochastic

Stochastic Constructor

StorageException - exception marf.Storage.StorageException.

Class StorageException

StorageException(String) - Constructor for class marf.Storage.StorageException

Generic exception

StorageManager - interface marf.Storage.StorageManager.

Interface StorageManager

saveSample(File) - Method in class marf.Storage.Loaders.MP3Loader

Not Implemented

saveSample(File) - Method in class marf.Storage.Loaders.ULAWLoader

Not Implemented

saveSample(File) - Method in class marf.Storage.Loaders.WAVLoader

Saves the wave into a file for playback

saveSample(File) - Method in class marf.Storage.SampleLoader

SampleLoader interface.

saveSample(String) - Method in class marf.Storage.SampleLoader

Same as saveSample(File) but takes filename as an argument.

setAll() - Method in class marf.math.Matrix

Default of 0.0

setAll(double) - Method in class marf.math.Matrix

Sets all elements of the matrix to the specified value.

setAudioFormat(int) - Method in class marf.Storage.Sample

Sets current format of a sample

setBorderedTitle(String) - Method in class marf.gui.util.BorderPanel

setClassificationMethod(int) - Static method in class marf.MARF

Sets classification method to be used

setClassificationParams(Vector) - Method in class marf.Storage.ModuleParams

Sets classification parameters vector

setCols(int) - Method in class marf.math.Matrix

setCurrentSubject(int) - Static method in class marf.MARF

Sets ID of a subject currently being trained on

setDataVector(double[]) - Method in class marf.Storage.TrainingSample

Sets new mean vector

setDirection(int) - Method in class marf.math.Matrix.Direction

Sets new value of current direction.

setDumpMode(int) - Method in class marf.Storage.TrainingSet

Sets the dump mode

setDumpSpectrogram(boolean) - Static method in class marf.MARF

Indicates whether spectrogram is wanted as an output of a FeatureExtraction module

setDumpWaveGraph(boolean) - Static method in class marf.MARF

Indicates whether wave graph is wanted as an output

setElement(int, int, double) - Method in class marf.math.Matrix

setElement(int, double) - Method in class marf.math.Vector

setFeatureExtractionMethod(int) - Static method in class marf.MARF

Sets feature extraction method to be used

setFeatureExtractionMethod(int) - Method in class marf.Storage.TrainingSet

Sets feature extraction method used on this training set

setFeatureExtractionParams(Vector) - Method in class marf.Storage.ModuleParams

Sets feature extraction parameters vector

setFilename(String) - Method in class marf.Storage.TrainingSample

Sets a filename of the training sample.

setFrequencyResponse(double[]) - Method in class marf.Preprocessing.FFTFilter.FFTFilter

Sets frequency response.

setID(int) - Method in class marf.Storage.Result

Sets ID, should only be called by a Classification module

setMatrix2D(double[][]) - Method in class marf.math.Matrix

Sets internal array based on 2-dimensional parameter.

setMatrixArray(double[]) - Method in class marf.math.Matrix

setMeanVector(double[]) - Method in class marf.Storage.Cluster

Sets new mean vector

setModuleParams(ModuleParams) - Static method in class marf.MARF

Sets module-specific parameters an application programmer wishes to pass on to the module

setPreprocessingMethod(int) - Static method in class marf.MARF

Sets preprocessing method to be used

setPreprocessingMethod(int) - Method in class marf.Storage.TrainingSet

Sets feature extraction method used on this training set

setPreprocessingParams(Vector) - Method in class marf.Storage.ModuleParams

Sets preprocessing parameters vector

setRows(int) - Method in class marf.math.Matrix

setSample(Sample) - Method in class marf.Storage.SampleLoader

Sets internal sample reference from outside

setSampleArray(double[]) - Method in class marf.Storage.Sample

Sets the internal sample array (adSample) with the specified argument.

setSampleFile(String) - Static method in class marf.MARF

Sets input sample file name

setSampleFormat(int) - Static method in class marf.MARF

Sets input sample file format

setSamplesDir(String) - Static method in class marf.MARF

Sets directory with sample files to be read from

setSubjectID(int) - Method in class marf.Storage.TrainingSample

Sets new Subject ID

setTrainingSetFile(String) - Method in class marf.Storage.TrainingSet

Sets current training set file name

siNextTID - Static variable in class marf.util.BaseThread

Next TID to be assigned.

size() - Method in class marf.Storage.FeatureSet

Sizes of the feature vectors set

size() - Method in class marf.Storage.TrainingSet

Gets the size of the feature vectors set

size() - Method in class marf.math.Matrix

Analoguous to getElements()

start() - Method in class marf.util.ExpandedThreadGroup

Starts all threads in this group.

strMessage - Variable in class marf.util.MARFException

Error message container

strMethod - Variable in class marf.gui.Spectrogram

To differentiate file names based on the feature extraction method name.

streamedRecognition() - Static method in class marf.MARF

Meant to provide implementation of the buffered sample processing for large samples.

T

TrainingSample - class marf.Storage.TrainingSample.

TrainingSample contains one item in the training set.

TrainingSample() - Constructor for class marf.Storage.TrainingSample

TrainingSet - class marf.Storage.TrainingSet.

TrainingSet -- Encapsulates Subject ID and subject's clusters or a feature set

TrainingSet() - Constructor for class marf.Storage.TrainingSet

Construct a training set object.

test - class test.

Nothing spectacular.

test() - Constructor for class test

threshold - Variable in class marf.Classification.NeuralNetwork.Neuron

Activation threshhold

toString() - Method in class marf.math.Matrix

Textual representation of the matrix

train() - Method in class marf.Classification.Classification

Generic training routine for building/updating mean vectors in the training set.

train() - Method in class marf.Classification.Markov.Markov

Not Implemented

train() - Method in class marf.Classification.NeuralNetwork.NeuralNetwork

Implementes training of Neural Net

train(double[], int, double) - Method in class marf.Classification.NeuralNetwork.NeuralNetwork

Actual training of the net

train(double, double, double) - Method in class marf.Classification.NeuralNetwork.Neuron

Neuron training

train() - Method in class marf.Classification.RandomClassification.RandomClassification

Simply stores incoming ID's

train() - Method in class marf.Classification.Stochastic.Stochastic

Not Implemented

train() - Static method in class marf.MARF

Training mode

transpose() - Method in class marf.math.Matrix

Matrix transpose

type - Variable in class marf.Classification.NeuralNetwork.Neuron

Current neuron type

U

ULAW - Static variable in class marf.MARF

Indicates ULAW incoming sample file format

ULAW - Static variable in class marf.Storage.Sample

ULAW sample format

ULAWLoader - class marf.Storage.Loaders.ULAWLoader.

Not Implemented

ULAWLoader() - Constructor for class marf.Storage.Loaders.ULAWLoader

ULAWLoader Constructor

UNDEF - Static variable in class marf.Classification.NeuralNetwork.Neuron

Indicates undefined neuron type

UNK - Static variable in class marf.Storage.Sample

Unknown sample format

updateSample() - Method in class marf.Storage.SampleLoader

UpdateSample() is just used whenever the AudioInputStream is assigned to a new value (wave file).

V

Vector - class marf.math.Vector.

Algebraic operations on vectors.

Vector() - Constructor for class marf.math.Vector

Vector(int) - Constructor for class marf.math.Vector

Vector(Vector) - Constructor for class marf.math.Vector

Vector(Matrix) - Constructor for class marf.math.Vector

Vector(double[]) - Constructor for class marf.math.Vector

W

W3C_XML_SCHEMA - Static variable in class marf.Classification.NeuralNetwork.NeuralNetwork

XML 2001 Schema

WAV - Static variable in class marf.MARF

Indicates WAV incoming sample file format

WAV - Static variable in class marf.Storage.Sample

WAVE sample format

WAVLoader - class marf.Storage.Loaders.WAVLoader.

Class WAVLoader

WAVLoader() - Constructor for class marf.Storage.Loaders.WAVLoader

WAVLoader Constructor.

WEST - Static variable in class marf.math.Matrix.Direction

WaveGrapher - class marf.gui.WaveGrapher.

Class WaveGrapher

WaveGrapher(double[], double, double, String, String) - Constructor for class marf.gui.WaveGrapher

Constructor

writeAudioData(double[], int) - Method in class marf.Storage.Loaders.MP3Loader

Not Implemented

writeAudioData(double[], int) - Method in class marf.Storage.Loaders.ULAWLoader

Not Implemented

writeAudioData(double[], int) - Method in class marf.Storage.Loaders.WAVLoader

Buffers the contents of audioData into audioBuffer

writeAudioData(double[], int) - Method in class marf.Storage.SampleLoader

Writes audio data into the sample's audio stream.

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