Inheritance diagram for FFT:

Public Types
enum	FFTWindowFunctionOptions { RECTANGULAR_WINDOW =0, BARTLETT_WINDOW, HAMMING_WINDOW, HANNING_WINDOW }

Public Types inherited from FeatureExtraction
typedef std::map< std::string, FeatureExtraction ()() >	StringFeatureExtractionMap

Public Types inherited from MLBase
enum	BaseType { BASE_TYPE_NOT_SET =0, CLASSIFIER, REGRESSIFIER, CLUSTERER, PRE_PROCSSING, POST_PROCESSING, FEATURE_EXTRACTION, CONTEXT }

Public Member Functions
	FFT (const UINT fftWindowSize=512, const UINT hopSize=1, const UINT numDimensions=1, const UINT fftWindowFunction=RECTANGULAR_WINDOW, const bool computeMagnitude=true, const bool computePhase=true)

	FFT (const FFT &rhs)

virtual	~FFT (void)

FFT &	operator= (const FFT &rhs)

virtual bool	deepCopyFrom (const FeatureExtraction *featureExtraction)

virtual bool	computeFeatures (const VectorFloat &inputVector)

virtual bool	computeFeatures (const MatrixFloat &inputMatrix)

virtual bool	clear ()

virtual bool	reset ()

virtual bool	save (std::fstream &file) const

virtual bool	load (std::fstream &file)

bool	init (const UINT fftWindowSize, const UINT hopSize=1, const UINT numDimensions=1, const UINT windowFunction=RECTANGULAR_WINDOW, const bool computeMagnitude=true, const bool computePhase=true, const DataType inputType=DATA_TYPE_VECTOR, const DataType outputType=DATA_TYPE_VECTOR)

bool	update (const Float x)

bool	update (const VectorFloat &x)

bool	update (const MatrixFloat &x)

UINT	getHopSize () const

UINT	getDataBufferSize () const

UINT	getFFTWindowSize () const

UINT	getFFTWindowFunction () const

UINT	getHopCounter () const

bool	getComputeMagnitude () const

bool	getComputePhase () const

Vector< FastFourierTransform >	getFFTResults () const

Vector< FastFourierTransform > &	getFFTResultsPtr ()

const Vector< FastFourierTransform > &	getFFTResultsPtr () const

VectorFloat	getFrequencyBins (const unsigned int sampleRate) const

bool	setHopSize (const UINT hopSize)

bool	setFFTWindowSize (const UINT fftWindowSize)

bool	setFFTWindowFunction (const UINT fftWindowFunction)

bool	setComputeMagnitude (const bool computeMagnitude)

bool	setComputePhase (const bool computePhase)

Public Member Functions inherited from FeatureExtraction
	FeatureExtraction (const std::string id="")

virtual	~FeatureExtraction ()

bool	copyBaseVariables (const FeatureExtraction *featureExtractionModule)

bool	getInitialized () const

bool	getFeatureDataReady () const

const VectorFloat &	getFeatureVector () const

const MatrixFloat &	getFeatureMatrix () const

FeatureExtraction *	create () const

	GRT_DEPRECATED_MSG ("createNewInstance is deprecated, use create() instead.", FeatureExtraction *createNewInstance() const )

	GRT_DEPRECATED_MSG ("createInstanceFromString(id) is deprecated, use create(id) instead.", static FeatureExtraction *createInstanceFromString(const std::string &id))

	GRT_DEPRECATED_MSG ("getFeatureExtractionType is deprecated, use getId() instead", std::string getFeatureExtractionType() const )

Public Member Functions inherited from MLBase
	MLBase (const std::string &id="", const BaseType type=BASE_TYPE_NOT_SET)

virtual	~MLBase (void)

bool	copyMLBaseVariables (const MLBase *mlBase)

virtual bool	train (ClassificationData trainingData)

virtual bool	train_ (ClassificationData &trainingData)

virtual bool	train (RegressionData trainingData)

virtual bool	train_ (RegressionData &trainingData)

virtual bool	train (RegressionData trainingData, RegressionData validationData)

virtual bool	train_ (RegressionData &trainingData, RegressionData &validationData)

virtual bool	train (TimeSeriesClassificationData trainingData)

virtual bool	train_ (TimeSeriesClassificationData &trainingData)

virtual bool	train (ClassificationDataStream trainingData)

virtual bool	train_ (ClassificationDataStream &trainingData)

virtual bool	train (UnlabelledData trainingData)

virtual bool	train_ (UnlabelledData &trainingData)

virtual bool	train (MatrixFloat data)

virtual bool	train_ (MatrixFloat &data)

virtual bool	predict (VectorFloat inputVector)

virtual bool	predict_ (VectorFloat &inputVector)

virtual bool	predict (MatrixFloat inputMatrix)

virtual bool	predict_ (MatrixFloat &inputMatrix)

virtual bool	map (VectorFloat inputVector)

virtual bool	map_ (VectorFloat &inputVector)

virtual bool	print () const

virtual bool	save (const std::string &filename) const

virtual bool	load (const std::string &filename)

	GRT_DEPRECATED_MSG ("saveModelToFile(std::string filename) is deprecated, use save(const std::string &filename) instead", virtual bool saveModelToFile(const std::string &filename) const )

	GRT_DEPRECATED_MSG ("saveModelToFile(std::fstream &file) is deprecated, use save(std::fstream &file) instead", virtual bool saveModelToFile(std::fstream &file) const )

	GRT_DEPRECATED_MSG ("loadModelFromFile(std::string filename) is deprecated, use load(const std::string &filename) instead", virtual bool loadModelFromFile(const std::string &filename))

	GRT_DEPRECATED_MSG ("loadModelFromFile(std::fstream &file) is deprecated, use load(std::fstream &file) instead", virtual bool loadModelFromFile(std::fstream &file))

virtual bool	getModel (std::ostream &stream) const

virtual std::string	getModelAsString () const

DataType	getInputType () const

DataType	getOutputType () const

BaseType	getType () const

UINT	getNumInputFeatures () const

UINT	getNumInputDimensions () const

UINT	getNumOutputDimensions () const

UINT	getMinNumEpochs () const

UINT	getMaxNumEpochs () const

UINT	getBatchSize () const

UINT	getNumRestarts () const

UINT	getValidationSetSize () const

UINT	getNumTrainingIterationsToConverge () const

Float	getMinChange () const

Float	getLearningRate () const

Float	getRMSTrainingError () const

	GRT_DEPRECATED_MSG ("getRootMeanSquaredTrainingError() is deprecated, use getRMSTrainingError() instead", Float getRootMeanSquaredTrainingError() const )

Float	getTotalSquaredTrainingError () const

Float	getRMSValidationError () const

Float	getValidationSetAccuracy () const

VectorFloat	getValidationSetPrecision () const

VectorFloat	getValidationSetRecall () const

bool	getUseValidationSet () const

bool	getRandomiseTrainingOrder () const

bool	getTrained () const

	GRT_DEPRECATED_MSG ("getModelTrained() is deprecated, use getTrained() instead", bool getModelTrained() const )

bool	getConverged () const

bool	getScalingEnabled () const

bool	getIsBaseTypeClassifier () const

bool	getIsBaseTypeRegressifier () const

bool	getIsBaseTypeClusterer () const

bool	getTrainingLoggingEnabled () const

bool	getTestingLoggingEnabled () const

bool	enableScaling (const bool useScaling)

bool	setMaxNumEpochs (const UINT maxNumEpochs)

bool	setBatchSize (const UINT batchSize)

bool	setMinNumEpochs (const UINT minNumEpochs)

bool	setNumRestarts (const UINT numRestarts)

bool	setMinChange (const Float minChange)

bool	setLearningRate (const Float learningRate)

bool	setUseValidationSet (const bool useValidationSet)

bool	setValidationSetSize (const UINT validationSetSize)

bool	setRandomiseTrainingOrder (const bool randomiseTrainingOrder)

bool	setTrainingLoggingEnabled (const bool loggingEnabled)

bool	setTestingLoggingEnabled (const bool loggingEnabled)

bool	registerTrainingResultsObserver (Observer< TrainingResult > &observer)

bool	registerTestResultsObserver (Observer< TestInstanceResult > &observer)

bool	removeTrainingResultsObserver (const Observer< TrainingResult > &observer)

bool	removeTestResultsObserver (const Observer< TestInstanceResult > &observer)

bool	removeAllTrainingObservers ()

bool	removeAllTestObservers ()

bool	notifyTrainingResultsObservers (const TrainingResult &data)

bool	notifyTestResultsObservers (const TestInstanceResult &data)

MLBase *	getMLBasePointer ()

const MLBase *	getMLBasePointer () const

Vector< TrainingResult >	getTrainingResults () const

Public Member Functions inherited from GRTBase
	GRTBase (const std::string &id="")

virtual	~GRTBase (void)

bool	copyGRTBaseVariables (const GRTBase *GRTBase)

	GRT_DEPRECATED_MSG ("getClassType is deprecated, use getId() instead!", std::string getClassType() const )

std::string	getId () const

std::string	getLastWarningMessage () const

std::string	getLastErrorMessage () const

std::string	getLastInfoMessage () const

bool	setInfoLoggingEnabled (const bool loggingEnabled)

bool	setWarningLoggingEnabled (const bool loggingEnabled)

bool	setErrorLoggingEnabled (const bool loggingEnabled)

bool	setDebugLoggingEnabled (const bool loggingEnabled)

GRTBase *	getGRTBasePointer ()

const GRTBase *	getGRTBasePointer () const

Float	scale (const Float &x, const Float &minSource, const Float &maxSource, const Float &minTarget, const Float &maxTarget, const bool constrain=false)

Float	SQR (const Float &x) const

Public Member Functions inherited from Observer< TrainingResult >
virtual void	notify (const TrainingResult &data)

Public Member Functions inherited from Observer< TestInstanceResult >
virtual void	notify (const TestInstanceResult &data)

Static Public Member Functions
static std::string	getId ()

Static Public Member Functions inherited from FeatureExtraction
static FeatureExtraction *	create (const std::string &id)

Static Public Member Functions inherited from GRTBase
static std::string	getGRTVersion (bool returnRevision=true)

static std::string	getGRTRevison ()

Protected Member Functions
bool	isPowerOfTwo (UINT x)
	A helper function to compute if the input is a power of two.

bool	validateFFTWindowFunction (UINT fftWindowFunction)

Protected Member Functions inherited from FeatureExtraction
bool	init ()

bool	saveFeatureExtractionSettingsToFile (std::fstream &file) const

bool	loadFeatureExtractionSettingsFromFile (std::fstream &file)

Protected Member Functions inherited from MLBase
bool	saveBaseSettingsToFile (std::fstream &file) const

bool	loadBaseSettingsFromFile (std::fstream &file)

Protected Attributes
UINT	hopSize
	The current hopSize, this sets how often the fft should be computed.

UINT	dataBufferSize
	Stores how much previous input data is stored in the dataBuffer.

UINT	fftWindowSize
	Stores the size of the fft (and also the dataBuffer)

UINT	fftWindowFunction
	The current windowFunction used for the FFT.

UINT	hopCounter
	Keeps track of how many input samples the FFT has seen.

bool	computeMagnitude
	Tracks if the magnitude (and power) of the FFT need to be computed.

bool	computePhase
	Tracks if the phase of the FFT needs to be computed.

VectorFloat	tempBuffer
	A temporary buffer used to store the input data for the FFT.

CircularBuffer< VectorFloat >	dataBuffer
	A circular buffer used to store the previous M inputs.

Vector< FastFourierTransform >	fft
	A buffer used to store the FFT results.

std::map< unsigned int, unsigned int >	windowSizeMap
	A map to relate the FFTWindowSize enumerations to actual values.

Protected Attributes inherited from FeatureExtraction
std::string	featureExtractionType

bool	initialized

bool	featureDataReady

VectorFloat	featureVector

MatrixFloat	featureMatrix

Protected Attributes inherited from MLBase
bool	trained

bool	useScaling

bool	converged

DataType	inputType

DataType	outputType

BaseType	baseType

UINT	numInputDimensions

UINT	numOutputDimensions

UINT	numTrainingIterationsToConverge

UINT	minNumEpochs

UINT	maxNumEpochs

UINT	batchSize

UINT	validationSetSize

UINT	numRestarts

Float	learningRate

Float	minChange

Float	rmsTrainingError

Float	rmsValidationError

Float	totalSquaredTrainingError

Float	validationSetAccuracy

bool	useValidationSet

bool	randomiseTrainingOrder

VectorFloat	validationSetPrecision

VectorFloat	validationSetRecall

Random	random

Vector< TrainingResult >	trainingResults

TrainingResultsObserverManager	trainingResultsObserverManager

TestResultsObserverManager	testResultsObserverManager

TrainingLog	trainingLog

TestingLog	testingLog

Protected Attributes inherited from GRTBase
std::string	classId
	Stores the name of the class (e.g., MinDist)

DebugLog	debugLog

ErrorLog	errorLog

InfoLog	infoLog

WarningLog	warningLog

Additional Inherited Members
Static Protected Member Functions inherited from FeatureExtraction
static StringFeatureExtractionMap *	getMap ()

Detailed Description

Examples:: FeatureExtractionModules/FFTExample/FFTExample.cpp.

Definition at line 57 of file FFT.h.

Constructor & Destructor Documentation

FFT::FFT	(	const UINT	fftWindowSize = `512`,
		const UINT	hopSize = `1`,
		const UINT	numDimensions = `1`,
		const UINT	fftWindowFunction = `RECTANGULAR_WINDOW`,
		const bool	computeMagnitude = `true`,
		const bool	computePhase = `true`
	)

Constructor, sets the fftWindowSize, hopSize, fftWindowFunction, if the magnitude and phase should be computed during the FFT and the number of dimensions in the input signal.

Parameters

fftWindowSize	sets the size of the fft, this should be a power of two. Default fftWindowSize=512
hopSize	sets how often the fft should be computed. If the hopSize parameter is set to 1 then the FFT will be computed everytime the classes computeFeatures(...) or computeFFT(...) functions are called. You may not want to compute the FFT of the input signal for every sample however, if this is the case then set the hopSize parameter to N, in which case the FFT will only be computed every N samples on the previous M values, where M is equal to the fftWindowSize. Default hopSize=1
numDimensions	the dimensionality of the input data to the FFT. Default numDimensions = 1
fftWindowFunction	sets the window function of the FFT. This should be one of the FFTWindowFunctionOptions enumeration values. Default windowFunction=RECTANGULAR_WINDOW
computeMagnitude	sets if the magnitude (and power) of the spectrum should be computed on the results of the FFT. Default computeMagnitude=true
computePhase	sets if the phase of the spectrum should be computed on the results of the FFT. Default computePhase=true

Definition at line 33 of file FFT.cpp.

FFT::FFT ( const FFT & rhs )

Copy Constructor, copies the FFT from the rhs instance to this instance

Parameters

rhs	another instance of the FFT class from which the data will be copied to this instance

Definition at line 46 of file FFT.cpp.

FFT::~FFT ( void )

virtual

Default Destructor

Definition at line 53 of file FFT.cpp.

Member Function Documentation

bool FFT::clear ( )

virtual

Sets the FeatureExtraction clear function, overwriting the base FeatureExtraction function. This function is called by the GestureRecognitionPipeline when the pipelines main clear() function is called. This function completely clears the FFT setup, you will need to initialize the instance again before you can use it.

Returns: true if the FFT was reset, false otherwise

Reimplemented from FeatureExtraction.

Definition at line 388 of file FFT.cpp.

bool FFT::computeFeatures ( const VectorFloat & inputVector )

virtual

Sets the FeatureExtraction computeFeatures function, overwriting the base FeatureExtraction function. This function is called by the GestureRecognitionPipeline when any new input data needs to be processed (during the prediction phase for example). This function calls the FFT's computeFFT(...) function.

Parameters

inputVector the inputVector that should be processed. Must have the same dimensionality as the FeatureExtraction module

Returns: true if the data was processed, false otherwise

Reimplemented from FeatureExtraction.

Definition at line 246 of file FFT.cpp.

bool FFT::computeFeatures ( const MatrixFloat & inputMatrix )

virtual

Sets the FeatureExtraction computeFeatures function, overwriting the base FeatureExtraction function. This function is called by the GestureRecognitionPipeline when any new input data needs to be processed (during the prediction phase for example). This function calls the FFT's computeFFT(...) function.

Parameters

inputMatrix the inputMatrix that should be processed. Must have the same dimensionality as the FeatureExtraction module

Returns: true if the data was processed, false otherwise

Reimplemented from FeatureExtraction.

Definition at line 250 of file FFT.cpp.

bool FFT::deepCopyFrom ( const FeatureExtraction * featureExtraction )

virtual

Sets the FeatureExtraction deepCopyFrom function, overwriting the base FeatureExtraction function. This function is used to deep copy the values from the input pointer to this instance of the FeatureExtraction module. This function is called by the GestureRecognitionPipeline when the user adds a new FeatureExtraction module to the pipeline.

Parameters

featureExtraction a pointer to another instance of an FFT, the values of that instance will be cloned to this instance

Returns: true if the deep copy was successful, false otherwise

Reimplemented from FeatureExtraction.

Definition at line 81 of file FFT.cpp.

bool FFT::getComputeMagnitude ( ) const

inline

Returns if the magnitude (and power) of the FFT spectrum is being computed.

Returns: true if the magnitude (and power) of the FFT spectrum is being computed and if the FFT has been initialized, otherwise false will be returned

Definition at line 252 of file FFT.h.

bool FFT::getComputePhase ( ) const

inline

Returns if the phase of the FFT spectrum is being computed.

Returns: true if the phase of the FFT spectrum is being computed and if the FFT has been initialized, otherwise false will be returned

Definition at line 259 of file FFT.h.

UINT FFT::getDataBufferSize ( ) const

Returns the current dataBufferSize, which is the same as the FFT window size.

Returns: returns the current dataBufferSize value if the FFT has been initialized, otherwise zero will be returned

Definition at line 411 of file FFT.cpp.

Vector< FastFourierTransform > FFT::getFFTResults ( ) const

inline

Returns the FFT results computed from the last FFT of the input signal.

Returns: returns a vector of FastFourierTransform (where the size of the vector is equal to the number of input dimensions for the FFT). An empty vector will be returned if the FFT was not computed

Examples:: FeatureExtractionModules/FFTExample/FFTExample.cpp.

Definition at line 266 of file FFT.h.

Vector< FastFourierTransform >& FFT::getFFTResultsPtr ( )

inline

Returns a pointer to the FFT results computed from the last FFT of the input signal.

Returns: returns a pointer to the vector of FastFourierTransform (where the size of the vector is equal to the number of input dimensions for the FFT). An empty vector will be returned if the FFT was not computed

Definition at line 273 of file FFT.h.

const Vector< FastFourierTransform >& FFT::getFFTResultsPtr ( ) const

inline

Returns a const pointer to the FFT results computed from the last FFT of the input signal.

Returns: returns a const pointer to the vector of FastFourierTransform (where the size of the vector is equal to the number of input dimensions for the FFT). An empty vector will be returned if the FFT was not computed

Definition at line 280 of file FFT.h.

UINT FFT::getFFTWindowFunction ( ) const

Returns the current FFT window function enumeration value.

Returns: returns the current FFT window function value if the FFT has been initialized, otherwise zero will be returned

Definition at line 422 of file FFT.cpp.

UINT FFT::getFFTWindowSize ( ) const

Returns the FFT window size.

Returns: returns the current FFT window size value if the FFT has been initialized, otherwise zero will be returned

Definition at line 416 of file FFT.cpp.

UINT FFT::getHopCounter ( ) const

Returns the current hop counter value.

Returns: returns the current hop counter value if the FFT has been initialized, otherwise zero will be returned

Definition at line 427 of file FFT.cpp.

UINT FFT::getHopSize ( ) const

Returns the current hopSize.

Returns: returns the current hopSize value if the FFT has been initialized, otherwise zero will be returned

Definition at line 406 of file FFT.cpp.

std::string FFT::getId ( )

static

Gets a string that represents the FFT class.

Returns: returns a string containing the ID of this class

Definition at line 28 of file FFT.cpp.

bool FFT::init	(	const UINT	fftWindowSize,
		const UINT	hopSize = `1`,
		const UINT	numDimensions = `1`,
		const UINT	windowFunction = `RECTANGULAR_WINDOW`,
		const bool	computeMagnitude = `true`,
		const bool	computePhase = `true`,
		const DataType	inputType = `DATA_TYPE_VECTOR`,
		const DataType	outputType = `DATA_TYPE_VECTOR`
	)

Initializes the FFT. Should be called before calling the computeFFT(...) or computeFeatures(...) methods. This function is automatically called by the constructor.

Parameters

fftWindowSize	sets the size of the fft, this must be a power of two
hopSize	sets how often the fft should be computed. If the hopSize parameter is set to 1 then the FFT will be computed everytime the classes computeFeatures(...) or computeFFT(...) functions are called. You may not want to compute the FFT of the input signal for every sample however, if this is the case then set the hopSize parameter to N, in which case the FFT will only be computed every N samples on the previous M values, where M is equal to the fftWindowSize
numDimensions	the dimensionality of the input data to the FFT
windowFunction	sets the window function of the FFT. This should be one of the WindowFunctionOptions enumeration values
computeMagnitude	sets if the magnitude (and power) of the spectrum should be computed on the results of the FFT
computePhase	sets if the phase of the spectrum should be computed on the results of the FFT
inputType	the input type expected, defaults to DATA_TYPE_VECTOR
outputType	the output type that can be accessed by users of the module, defaults to DATA_TYPE_VECTOR

Returns: true if the FTT was initialized, false otherwise

Definition at line 185 of file FFT.cpp.

bool FFT::load ( std::fstream & file )

virtual

This loads the feature extraction settings from a file. This overrides the load function in the FeatureExtraction base class.

Parameters

file	a reference to the file to load the settings from

Returns: returns true if the settings were loaded successfully, false otherwise

Reimplemented from MLBase.

Definition at line 124 of file FFT.cpp.

FFT & FFT::operator= ( const FFT & rhs )

Sets the equals operator, copies the data from the rhs instance to this instance

Parameters

rhs	another instance of the FFT class from which the data will be copied to this instance

Returns: a reference to this instance of FFT

Definition at line 56 of file FFT.cpp.

bool FFT::reset ( )

virtual

Sets the FeatureExtraction reset function, overwriting the base FeatureExtraction function. This function is called by the GestureRecognitionPipeline when the pipelines main reset() function is called. This function resets the FFT by re-initiliazing the instance.

Returns: true if the FFT was reset, false otherwise

Reimplemented from MLBase.

Definition at line 401 of file FFT.cpp.

bool FFT::save ( std::fstream & file ) const

virtual

This saves the feature extraction settings to a file. This overrides the save function in the FeatureExtraction base class.

Parameters

file	a reference to the file to save the settings to

Returns: returns true if the settings were saved successfully, false otherwise

Reimplemented from MLBase.

Definition at line 98 of file FFT.cpp.

bool FFT::setComputeMagnitude ( const bool computeMagnitude )

Sets if the magnitude (and power) of the FFT spectrum should be computed.

Parameters

computeMagnitude the new computeMagnitude parameter

Returns: returns true if the computeMagnitude parameter was successfully updated, false otherwise

Definition at line 471 of file FFT.cpp.

bool FFT::setComputePhase ( const bool computePhase )

Sets if the phase of the FFT spectrum should be computed.

Parameters

computePhase the new computeMagnitude parameter

Returns: returns true if the computePhase parameter was successfully updated, false otherwise

Definition at line 477 of file FFT.cpp.

bool FFT::setFFTWindowFunction ( const UINT fftWindowFunction )

Sets the fftWindowFunction parameter, this should be one of the FFTWindowFunctionOptions enumeration values.

Parameters

fftWindowFunction the new fftWindowFunction parameter, must be one of the FFTWindowFunctionOptions enumeration values

Returns: returns true if the fftWindowFunction parameter was successfully updated, false otherwise

Definition at line 463 of file FFT.cpp.

bool FFT::setFFTWindowSize ( const UINT fftWindowSize )

Sets the fftWindowSize parameter, this sets the size of the fft, this must be a power of two. Setting this value will also re-initialize the FFT.

Parameters

fftWindowSize the new fftWindowSize parameter, this must be a power of two.

Returns: returns true if the fftWindowSize parameter was successfully updated, false otherwise

Definition at line 452 of file FFT.cpp.

bool FFT::setHopSize ( const UINT hopSize )

Sets the hopSize parameter, this sets how often the fft should be computed. If the hopSize parameter is set to 1 then the FFT will be computed everytime the classes' computeFeatures(...) or computeFFT(...) functions are called. You may not want to compute the FFT of the input signal for every sample however, if this is the case then set the hopSize parameter to N, in which case the FFT will only be computed every N samples on the previous M values, where M is equal to the fftWindowSize. The hopSize must be greater than zero. Setting the hopSize will also reset the hop counter.

Parameters

hopSize the new hopSize parameter, must be greater than zero

Returns: returns true if the hopSize parameter was successfully updated, false otherwise

Definition at line 442 of file FFT.cpp.

bool FFT::update ( const Float x )

Computes the FFT of the previous M input samples, where M is the size of the fft window set by the constructor. The FFT of the input will only be computed if the current hop counter value matches the hopSize. This function should only be used if the dimensionality of the FFT has been set to 1.

Parameters

x	the new sample, this will be added to a buffer and the FFT will be computed for the data in the buffer

Returns: true if the FTT was updated successfully, false otherwise

Examples:: FeatureExtractionModules/FFTExample/FFTExample.cpp.

Definition at line 254 of file FFT.cpp.

bool FFT::update ( const VectorFloat & x )

Computes the FFT of the previous M input samples, where M is the size of the fft window set by the constructor. The FFT of the input will only be computed if the current hop counter value matches the hopSize. The dimensionality of the input vector must match the number of dimensions for the FFT.

Parameters

x	the new N-dimensional sample, this will be added to a buffer and the FFT will be computed for the data in the buffer

Returns: true if the FTT was updated successfully, false otherwise

Definition at line 269 of file FFT.cpp.

bool FFT::update ( const MatrixFloat & x )

Computes the FFT of the previous M input samples, where M is the size of the fft window set by the constructor. The FFT of the input will only be computed if the current hop counter value matches the hopSize. The number of columns in the input matrix must match the number of dimensions for the FFT.

Parameters

x	a [M N] matrix, this will be added to a buffer and the FFT will be computed for the data in the buffer

Returns: true if the FTT was updated successfully, false otherwise

Definition at line 327 of file FFT.cpp.

The documentation for this class was generated from the following files:

Public Types

Public Member Functions

Static Public Member Functions

Protected Member Functions

Protected Attributes

Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

Member Function Documentation