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GestureRecognitionToolkit
Version: 1.0 Revision: 04-03-15
The Gesture Recognition Toolkit (GRT) is a cross-platform, open-source, c++ machine learning library for real-time gesture recognition.
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This is the complete list of members for GRT::FFT, including all inherited members.
BARTLETT_WINDOW enum value (defined in GRT::FFT) | GRT::FFT | |
BASE_TYPE_NOT_SET enum value (defined in GRT::MLBase) | GRT::MLBase | |
baseType (defined in GRT::MLBase) | GRT::MLBase | protected |
BaseTypes enum name (defined in GRT::MLBase) | GRT::MLBase | |
CLASSIFIER enum value (defined in GRT::MLBase) | GRT::MLBase | |
classType (defined in GRT::GRTBase) | GRT::GRTBase | protected |
clear() | GRT::FFT | virtual |
CLUSTERER enum value (defined in GRT::MLBase) | GRT::MLBase | |
computeFeatures(const VectorDouble &inputVector) | GRT::FFT | virtual |
computeMagnitude | GRT::FFT | protected |
computePhase | GRT::FFT | protected |
copyBaseVariables(const FeatureExtraction *featureExtractionModule) | GRT::FeatureExtraction | |
copyGRTBaseVariables(const GRTBase *GRTBase) | GRT::GRTBase | |
copyMLBaseVariables(const MLBase *mlBase) | GRT::MLBase | |
createInstanceFromString(string const &featureExtractionType) (defined in GRT::FeatureExtraction) | GRT::FeatureExtraction | static |
createNewInstance() const | GRT::FeatureExtraction | |
dataBuffer | GRT::FFT | protected |
dataBufferSize | GRT::FFT | protected |
debugLog (defined in GRT::GRTBase) | GRT::GRTBase | protected |
deepCopyFrom(const FeatureExtraction *featureExtraction) | GRT::FFT | virtual |
enableScaling(bool useScaling) | GRT::MLBase | |
errorLog (defined in GRT::GRTBase) | GRT::GRTBase | protected |
featureDataReady (defined in GRT::FeatureExtraction) | GRT::FeatureExtraction | protected |
FeatureExtraction() | GRT::FeatureExtraction | |
featureExtractionType (defined in GRT::FeatureExtraction) | GRT::FeatureExtraction | protected |
featureVector (defined in GRT::FeatureExtraction) | GRT::FeatureExtraction | protected |
FFT(UINT fftWindowSize=512, UINT hopSize=1, UINT numDimensions=1, UINT fftWindowFunction=RECTANGULAR_WINDOW, bool computeMagnitude=true, bool computePhase=true) | GRT::FFT | |
FFT(const FFT &rhs) | GRT::FFT | |
fft | GRT::FFT | protected |
fftWindowFunction | GRT::FFT | protected |
FFTWindowFunctionOptions enum name (defined in GRT::FFT) | GRT::FFT | |
fftWindowSize | GRT::FFT | protected |
getBaseType() const | GRT::MLBase | |
getClassType() const | GRT::GRTBase | |
getComputeMagnitude() | GRT::FFT | inline |
getComputePhase() | GRT::FFT | inline |
getDataBufferSize() | GRT::FFT | |
getFeatureDataReady() const | GRT::FeatureExtraction | |
getFeatureExtractionType() const | GRT::FeatureExtraction | |
getFeatureVector() const | GRT::FeatureExtraction | |
getFFTResults() | GRT::FFT | inline |
getFFTResultsPtr() | GRT::FFT | inline |
getFFTWindowFunction() | GRT::FFT | |
getFFTWindowSize() | GRT::FFT | |
getFrequencyBins(const unsigned int sampleRate) (defined in GRT::FFT) | GRT::FFT | |
getGRTBasePointer() | GRT::GRTBase | |
getGRTBasePointer() const | GRT::GRTBase | |
getGRTRevison() | GRT::GRTBase | static |
getGRTVersion(bool returnRevision=true) | GRT::GRTBase | static |
getHopCounter() | GRT::FFT | |
getHopSize() | GRT::FFT | |
getInitialized() const | GRT::FeatureExtraction | |
getIsBaseTypeClassifier() const | GRT::MLBase | |
getIsBaseTypeClusterer() const | GRT::MLBase | |
getIsBaseTypeRegressifier() const | GRT::MLBase | |
getLastErrorMessage() const | GRT::GRTBase | |
getLastInfoMessage() const | GRT::GRTBase | |
getLastWarningMessage() const | GRT::GRTBase | |
getLearningRate() const | GRT::MLBase | |
getMap() (defined in GRT::FeatureExtraction) | GRT::FeatureExtraction | inlineprotectedstatic |
getMaxNumEpochs() const | GRT::MLBase | |
getMinChange() const | GRT::MLBase | |
getMinNumEpochs() const | GRT::MLBase | |
getMLBasePointer() | GRT::MLBase | |
getMLBasePointer() const | GRT::MLBase | |
getModel(ostream &stream) const | GRT::MLBase | virtual |
getModelAsString() const | GRT::MLBase | virtual |
getModelTrained() const | GRT::MLBase | |
getNumInputDimensions() const | GRT::FeatureExtraction | |
getNumInputFeatures() const | GRT::MLBase | |
getNumOutputDimensions() const | GRT::FeatureExtraction | |
getNumTrainingIterationsToConverge() const | GRT::MLBase | |
getRandomiseTrainingOrder() const | GRT::MLBase | |
getRootMeanSquaredTrainingError() const | GRT::MLBase | |
getScalingEnabled() const | GRT::MLBase | |
getTotalSquaredTrainingError() const | GRT::MLBase | |
getTrained() const | GRT::MLBase | |
getTrainingResults() const | GRT::MLBase | |
getUseValidationSet() const | GRT::MLBase | |
getValidationSetSize() const | GRT::MLBase | |
GRTBase(void) | GRT::GRTBase | |
HAMMING_WINDOW enum value (defined in GRT::FFT) | GRT::FFT | |
HANNING_WINDOW enum value (defined in GRT::FFT) | GRT::FFT | |
hopCounter | GRT::FFT | protected |
hopSize | GRT::FFT | protected |
infoLog (defined in GRT::GRTBase) | GRT::GRTBase | protected |
init(UINT fftWindowSize, UINT hopSize, UINT numDimensions, UINT windowFunction, bool computeMagnitude, bool computePhase) | GRT::FFT | |
GRT::FeatureExtraction::init() | GRT::FeatureExtraction | protected |
initialized (defined in GRT::FeatureExtraction) | GRT::FeatureExtraction | protected |
isPowerOfTwo(UINT x) | GRT::FFT | protected |
learningRate (defined in GRT::MLBase) | GRT::MLBase | protected |
load(const string filename) | GRT::MLBase | virtual |
loadBaseSettingsFromFile(fstream &file) | GRT::MLBase | protected |
loadFeatureExtractionSettingsFromFile(fstream &file) | GRT::FeatureExtraction | protected |
loadModelFromFile(fstream &file) | GRT::FFT | virtual |
GRT::MLBase::loadModelFromFile(string filename) | GRT::MLBase | virtual |
map(VectorDouble inputVector) | GRT::MLBase | virtual |
map_(VectorDouble &inputVector) | GRT::MLBase | virtual |
maxNumEpochs (defined in GRT::MLBase) | GRT::MLBase | protected |
minChange (defined in GRT::MLBase) | GRT::MLBase | protected |
minNumEpochs (defined in GRT::MLBase) | GRT::MLBase | protected |
MLBase(void) | GRT::MLBase | |
notify(const TrainingResult &data) (defined in GRT::Observer< TrainingResult >) | GRT::Observer< TrainingResult > | inlinevirtual |
notify(const TestInstanceResult &data) (defined in GRT::Observer< TestInstanceResult >) | GRT::Observer< TestInstanceResult > | inlinevirtual |
notifyTestResultsObservers(const TestInstanceResult &data) | GRT::MLBase | |
notifyTrainingResultsObservers(const TrainingResult &data) | GRT::MLBase | |
numInputDimensions (defined in GRT::MLBase) | GRT::MLBase | protected |
numOutputDimensions (defined in GRT::MLBase) | GRT::MLBase | protected |
numTrainingIterationsToConverge (defined in GRT::MLBase) | GRT::MLBase | protected |
Observer() (defined in GRT::Observer< TrainingResult >) | GRT::Observer< TrainingResult > | inline |
Observer() (defined in GRT::Observer< TestInstanceResult >) | GRT::Observer< TestInstanceResult > | inline |
operator=(const FFT &rhs) | GRT::FFT | |
predict(VectorDouble inputVector) | GRT::MLBase | virtual |
predict(MatrixDouble inputMatrix) | GRT::MLBase | virtual |
predict_(VectorDouble &inputVector) | GRT::MLBase | virtual |
predict_(MatrixDouble &inputMatrix) | GRT::MLBase | virtual |
print() const | GRT::MLBase | virtual |
random (defined in GRT::MLBase) | GRT::MLBase | protected |
randomiseTrainingOrder (defined in GRT::MLBase) | GRT::MLBase | protected |
RECTANGULAR_WINDOW enum value (defined in GRT::FFT) | GRT::FFT | |
registerModule (defined in GRT::FFT) | GRT::FFT | protectedstatic |
registerTestResultsObserver(Observer< TestInstanceResult > &observer) | GRT::MLBase | |
registerTrainingResultsObserver(Observer< TrainingResult > &observer) | GRT::MLBase | |
REGRESSIFIER enum value (defined in GRT::MLBase) | GRT::MLBase | |
removeAllTestObservers() | GRT::MLBase | |
removeAllTrainingObservers() | GRT::MLBase | |
removeTestResultsObserver(const Observer< TestInstanceResult > &observer) | GRT::MLBase | |
removeTrainingResultsObserver(const Observer< TrainingResult > &observer) | GRT::MLBase | |
reset() | GRT::FFT | virtual |
rootMeanSquaredTrainingError (defined in GRT::MLBase) | GRT::MLBase | protected |
save(const string filename) const | GRT::MLBase | virtual |
saveBaseSettingsToFile(fstream &file) const | GRT::MLBase | protected |
saveFeatureExtractionSettingsToFile(fstream &file) const | GRT::FeatureExtraction | protected |
saveModelToFile(fstream &file) const | GRT::FFT | virtual |
GRT::MLBase::saveModelToFile(string filename) const | GRT::MLBase | virtual |
scale(const double &x, const double &minSource, const double &maxSource, const double &minTarget, const double &maxTarget, const bool constrain=false) | GRT::MLBase | inline |
setComputeMagnitude(bool computeMagnitude) | GRT::FFT | |
setComputePhase(bool computePhase) | GRT::FFT | |
setFFTWindowFunction(UINT fftWindowFunction) | GRT::FFT | |
setFFTWindowSize(UINT fftWindowSize) | GRT::FFT | |
setHopSize(UINT hopSize) | GRT::FFT | |
setLearningRate(double learningRate) | GRT::MLBase | |
setMaxNumEpochs(const UINT maxNumEpochs) | GRT::MLBase | |
setMinChange(const double minChange) | GRT::MLBase | |
setMinNumEpochs(const UINT minNumEpochs) | GRT::MLBase | |
setRandomiseTrainingOrder(const bool randomiseTrainingOrder) | GRT::MLBase | |
setUseValidationSet(const bool useValidationSet) | GRT::MLBase | |
setValidationSetSize(const UINT validationSetSize) | GRT::MLBase | |
SQR(const double &x) const (defined in GRT::GRTBase) | GRT::GRTBase | inlineprotected |
StringFeatureExtractionMap typedef | GRT::FeatureExtraction | |
tempBuffer | GRT::FFT | protected |
testingLog (defined in GRT::GRTBase) | GRT::GRTBase | protected |
testResultsObserverManager (defined in GRT::MLBase) | GRT::MLBase | protected |
totalSquaredTrainingError (defined in GRT::MLBase) | GRT::MLBase | protected |
train(ClassificationData trainingData) | GRT::MLBase | virtual |
train(RegressionData trainingData) | GRT::MLBase | virtual |
train(TimeSeriesClassificationData trainingData) | GRT::MLBase | virtual |
train(TimeSeriesClassificationDataStream trainingData) | GRT::MLBase | virtual |
train(UnlabelledData trainingData) | GRT::MLBase | virtual |
train(MatrixDouble data) | GRT::MLBase | virtual |
train_(ClassificationData &trainingData) | GRT::MLBase | virtual |
train_(RegressionData &trainingData) | GRT::MLBase | virtual |
train_(TimeSeriesClassificationData &trainingData) | GRT::MLBase | virtual |
train_(TimeSeriesClassificationDataStream &trainingData) | GRT::MLBase | virtual |
train_(UnlabelledData &trainingData) | GRT::MLBase | virtual |
train_(MatrixDouble &data) | GRT::MLBase | virtual |
trained (defined in GRT::MLBase) | GRT::MLBase | protected |
trainingLog (defined in GRT::GRTBase) | GRT::GRTBase | protected |
trainingResults (defined in GRT::MLBase) | GRT::MLBase | protected |
trainingResultsObserverManager (defined in GRT::MLBase) | GRT::MLBase | protected |
update(const double x) | GRT::FFT | |
update(const VectorDouble &x) | GRT::FFT | |
useScaling (defined in GRT::MLBase) | GRT::MLBase | protected |
useValidationSet (defined in GRT::MLBase) | GRT::MLBase | protected |
validateFFTWindowFunction(UINT fftWindowFunction) (defined in GRT::FFT) | GRT::FFT | protected |
validationSetSize (defined in GRT::MLBase) | GRT::MLBase | protected |
warningLog (defined in GRT::GRTBase) | GRT::GRTBase | protected |
windowSizeMap | GRT::FFT | protected |
~FeatureExtraction() | GRT::FeatureExtraction | virtual |
~FFT(void) | GRT::FFT | virtual |
~GRTBase(void) | GRT::GRTBase | virtual |
~MLBase(void) | GRT::MLBase | virtual |
~Observer() (defined in GRT::Observer< TrainingResult >) | GRT::Observer< TrainingResult > | inlinevirtual |
~Observer() (defined in GRT::Observer< TestInstanceResult >) | GRT::Observer< TestInstanceResult > | inlinevirtual |