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Class JSci.maths.wavelet.Signal

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

public class Signal

extends LinearSpline

implements NumericalConstants, Cloneable

Signal()

Signal(double[])

Signal(Filter)

Signal(Filter, double[])

Signal(Filter, double[], double[])

absFFT()

Return the absolute value of the FFT

absFFT(double[])

clone()

Return a copy of this object

denoiseByFFT(int)

Simplistic FFT denoising.

denoiseShortPeaks(double, int)

This denoising method will identify "short peaks" in the signal and take them away.

entropy()

Return the entropy of the signal

equals(Signal)

Check if another object is equal to this Signal object

fft()

fft(Complex[])

fft(double[])

This is merely a copy of the FFT method found in the class FourierMath with some changes...

fftInverse(Complex[])

Also noted iFFT in other packages.

filter(double[])

Apply the given array as a convolution Filter and return a new Signal.

fwt(int)

Fast Wavelet Transform

fwtPacket(int, NMapping)

The Fast Wavelet Transform with Wavelet packets

getValues()

Get the sampled values of the sample as an array.

highpassProject()

Project the signal according the the highpass Filter

lowpassProject()

Project the data according to the lowpass Filter

medianFilter(int)

Apply the median Filter of a window of size 2*n+1.

norm()

Compute the L2 norm of the signal

removeParameter()

Throws away the parameter of the Filter

resample(int)

Resample the signal using linear interpolation

setData(double[])

Set the data for the signal

setDimensionFromBeginning(int)

Will make the signal a given dimension

setDimensionFromEnd(int)

Will make the signal a given dimension

setFilter(Filter)

set the signal associated Filter

setLengthFromBeginning(int)

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

setLengthFromEnd(int)

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

setParameter(Double[])

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

setParameter(double[])

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

 public Signal()

 public Signal(double v[])

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

 public Signal(Filter f)

 public Signal(Filter f,
               double v[])

 public Object clone()

Return a copy of this object

Overrides:

clone in class LinearSpline

 public double[] getValues()

Get the sampled values of the sample as an array.

 public void setFilter(Filter f)

set the signal associated Filter

 public void setParameter(double p[])

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

 public void setParameter(Double p[])

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

 public void removeParameter()

Throws away the parameter of the Filter

 public void setLengthFromEnd(int longueur)

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

 public void resample(int newl)

Resample the signal using linear interpolation

 public void setLengthFromBeginning(int longueur)

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

 public void setData(double v[])

Set the data for the signal

 public FWTCoef fwt(int J)

Fast Wavelet Transform

 public FWTPacketCoef fwtPacket(int J,
                                NMapping cout)

The Fast Wavelet Transform with Wavelet packets

Parameters:

J - number of iterations

cout - cost function

 public double[] lowpassProject()

Project the data according to the lowpass Filter

 public double[] highpassProject()

Project the signal according the the highpass Filter

 public double norm()

Compute the L2 norm of the signal

 public Complex[] fft()

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

This is merely a copy of the FFT method found in the class FourierMath with some changes... optimized for double[] arrays.

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

 public double[] absFFT()

Return the absolute value of the FFT

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

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

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

 public boolean equals(Signal b)

Check if another object is equal to this Signal object

 public void setDimensionFromEnd(int dimension)

Will make the signal a given dimension

 public void setDimensionFromBeginning(int dimension)

Will make the signal a given dimension

 public void denoiseByFFT(int k)

Simplistic FFT denoising.

Parameters:

k - frequency to denoised

 public double entropy()

Return the entropy of the signal

 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

 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

 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

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