JSci.maths.wavelet
Class Signal

java.lang.Object
  JSci.maths.wavelet.MultiscaleFunction
      JSci.maths.wavelet.splines.Spline
          JSci.maths.wavelet.splines.LinearSpline
              JSci.maths.wavelet.Signal

All Implemented Interfaces:

java.lang.Cloneable, NumericalConstants, Filter

public class Signal
extends LinearSpline
implements NumericalConstants, java.lang.Cloneable

This class use the linear spline as a general model for a signal. While this is a reasonnable design choice, this can certainly be overwritten if necessary. Basic operations on signal are supported.

Field Summary

(package private) static double

normalisation

Fields inherited from class JSci.maths.wavelet.splines.LinearSpline

filtretype

Fields inherited from interface JSci.maths.NumericalConstants

GAMMA, GOLDEN_RATIO, LOG10, SQRT2, SQRT2PI, TWO_PI

Constructor Summary

Signal()

Signal(double[] v)

Signal(Filter f)

Signal(Filter f, double[] v)

Signal(Filter f, double[] v, double[] p)

Method Summary

double[]	absFFT() Return the absolute value of the FFT
static double[]	absFFT(double[] data)
java.lang.Object	clone() Return a copy of this object
void	denoiseByFFT(int k) Simplistic FFT denoising.
Signal	denoiseShortPeaks(double p, int n) This denoising method will identify "short peaks" in the signal and take them away.
double	entropy() Return the entropy of the signal
boolean	equals(Signal b) Check if another object is equal to this Signal object
Complex[]	fft()
static Complex[]	fft(Complex[] data) Performs the Fourier transform.
static Complex[]	fft(double[] data) Performs the Fourier transform.
static Complex[]	fftInverse(Complex[] data) Also noted iFFT in other packages.
Signal	filter(double[] f) Apply the given array as a convolution Filter and return a new Signal.
FWTCoef	fwt(int J) Fast Wavelet Transform
FWTPacketCoef	fwtPacket(int J, MappingND cout) The Fast Wavelet Transform with Wavelet packets
double[]	getValues() Get the sampled values of the sample as an array.
double[]	highpassProject() Project the signal according the the highpass Filter
double[]	lowpassProject() Project the data according to the lowpass Filter
Signal	medianFilter(int n) Apply the median Filter of a window of size 2*n+1.
double	norm() Compute the L2 norm of the signal
void	removeParameters() Throws away the parameters of the Filter
void	resample(int newl) Resample the signal using linear interpolation
void	setData(double[] v) Set the data for the signal
void	setDimensionFromBeginning(int dimension) Will make the signal a given dimension
void	setDimensionFromEnd(int dimension) Will make the signal a given dimension
void	setFilter(Filter f) set the signal associated Filter
void	setLengthFromBeginning(int longueur) Set the Signal to the specified length scraping or padding the end if necessary
void	setLengthFromEnd(int longueur) Set the Signal to the specified length scraping or padding the beginning if necessary
void	setParameters(double[] p) Set the parameter of the Filter (if it applies).
void	setParameters(java.lang.Double[] p) Set the parameters of the Filter (if it applies).

Methods inherited from class JSci.maths.wavelet.splines.LinearSpline

derive, derive, dimension, dimension, equals, evaluate, getFilterType, getValue, highpass, highpass, interpolate, lowpass, lowpass, previousDimension, setValue, setValues, toString

Methods inherited from class JSci.maths.wavelet.MultiscaleFunction

mass, mass

Methods inherited from class java.lang.Object

finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Field Detail

normalisation

static final double normalisation

See Also:

Constant Field Values

Constructor Detail

Signal

public Signal()

Signal

public Signal(double[] v)

Signal

public Signal(Filter f,
              double[] v,
              double[] p)

Signal

public Signal(Filter f)

Signal

public Signal(Filter f,
              double[] v)

Method Detail

clone

public java.lang.Object clone()

Return a copy of this object

Overrides:

clone in class LinearSpline

getValues

public double[] getValues()

Get the sampled values of the sample as an array.

setFilter

public void setFilter(Filter f)

set the signal associated Filter

setParameters

public void setParameters(double[] p)

Set the parameter of the Filter (if it applies).

setParameters

public void setParameters(java.lang.Double[] p)

Set the parameters of the Filter (if it applies).

removeParameters

public void removeParameters()

Throws away the parameters of the Filter

setLengthFromEnd

public void setLengthFromEnd(int longueur)

Set the Signal to the specified length scraping or padding the beginning if necessary

resample

public void resample(int newl)

Resample the signal using linear interpolation

setLengthFromBeginning

public void setLengthFromBeginning(int longueur)

Set the Signal to the specified length scraping or padding the end if necessary

setData

public void setData(double[] v)

Set the data for the signal

fwt

public FWTCoef fwt(int J)

Fast Wavelet Transform

fwtPacket

public FWTPacketCoef fwtPacket(int J,
                               MappingND cout)

The Fast Wavelet Transform with Wavelet packets

Parameters:

J - number of iterations

cout - cost function

lowpassProject

public double[] lowpassProject()

Project the data according to the lowpass Filter

highpassProject

public double[] highpassProject()

Project the signal according the the highpass Filter

norm

public double norm()

Compute the L2 norm of the signal

fft

public Complex[] fft()

fft

public static Complex[] fft(double[] data)

Performs the Fourier transform. Convenience method for FourierMath.transform.

fft

public static Complex[] fft(Complex[] data)

Performs the Fourier transform. Convenience method for FourierMath.transform.

absFFT

public double[] absFFT()

Return the absolute value of the FFT

absFFT

public static double[] absFFT(double[] data)

fftInverse

public static Complex[] fftInverse(Complex[] data)

Also noted iFFT in other packages. This is the inverse to the FFT.

equals

public boolean equals(Signal b)

Check if another object is equal to this Signal object

setDimensionFromEnd

public void setDimensionFromEnd(int dimension)

Will make the signal a given dimension

setDimensionFromBeginning

public void setDimensionFromBeginning(int dimension)

Will make the signal a given dimension

denoiseByFFT

public void denoiseByFFT(int k)

Simplistic FFT denoising.

Parameters:

k - frequency to denoised

entropy

public double entropy()

Return the entropy of the signal

filter

public Signal filter(double[] f)

Apply the given array as a convolution Filter and return a new Signal. As one often want to compare the result to the original signal, this method is "safe", that is, it won't change the current object.

Parameters:

f - an array containing the coefficients of the convolution Filter

medianFilter

public Signal medianFilter(int n)

Apply the median Filter of a window of size 2*n+1. exception IllegalArgumentException if the parameter n is negative

denoiseShortPeaks

public Signal denoiseShortPeaks(double p,
                                int n)

This denoising method will identify "short peaks" in the signal and take them away. Short peaks are defined from a comparison with the median filtered signal. Only "significative" peaks are detected (see parameter p). This method won't denoise near the boundaries. "Short" refers here to the time-domain and not the amplitude. param p percentage of the range (max-min) considered as a significative step param n length of the peak in the time domain exception IllegalArgumentException if p is not between 0 and 1 exception IllegalArgumentException if the parameter n is negative