Documentation of 'jsci.maths.wavelet.Signal' Java class
Signal
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jsci.maths.wavelet

Class 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.

    • 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

      • 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
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