    All Packages  Class Hierarchy  This Package  Previous  Next  Index

# 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

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.

##

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).

##

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[])

##

clone

     public 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

setParameter

     public void setParameter(double p[])

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

setParameter

     public void setParameter(Double p[])

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

removeParameter

     public void removeParameter()

  Throws away the parameter 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,
                                    NMapping 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[])

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

fft

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

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

    All Packages  Class Hierarchy  This Package  Previous  Next  Index