MORSEWAVE is the jWavelet module of jLab.

  MORSEWAVE  Generalized Morse wavelets of Olhede and Walden (2002). 
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    PSI=MORSEWAVE(N,GAMMA,BETA,FS) returns an  N x LENGTH(FS) array PSI 
    which contains time-domain versions of the generalized Morse wavelet
    specified by GAMMA and BETA, concentrated at frequencies FS.
   
    The vector FS specifically denote the *radian* frequencies at which 
    the Fourier transform of the wavelets reach their maximum amplitudes.  
 
    A set of frequencies appropriate for analyzing a given length time 
    series can be easily chosen using MORSESPACE.
 
    Note that the wavelets are centered at the midpoint in time, that is, 
    row number ROUND(SIZE(PSI,1)/2).  FS assumes a unit sample rate. 
 
    [PSI,PSIF]=MORSEWAVE(...) optionally returns a frequency-domain version
    PSIF of the wavelets.  PSIF is the same size as PSI.
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    Normalization
 
    MORSEWAVE supports two kinds of normalization for the wavelets.
 
    MORSEWAVE(...,'bandpass') uses "bandpass normalization", meaning that
    the FFT of the wavelet has a peak value of 2 for all frequencies FS. 
 
    MORSEWAVE(...,'energy') uses the unit energy normalization.  The time-
    domain wavelet energy SUM(ABS(PSI).^2,1) is then always unity. 
 
    The bandpass normalization corresponds to having 1/S in the time-domain
    wavelet transform defintion, where S is the scale, while the unit 
    energy normalization corresponds to 1/SQRT(S).
 
    MORSEWAVE uses bandpass normalization by default.
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    Multiple orthogonal wavelets 
 
    MORSEWAVE can compute multiple orthogonal versions of the generalized
    Morse wavelets, characterized by the order K.
 
    PSI=MORSEWAVE(N,K,GAMMA,BETA,FS) with a fifth numerical argument K
    returns an N x LENGTH(FS) x K array PSI which contains time-domain 
    versions of the first K orthogonal generalized Morse wavelets.
 
    These K different orthogonal wavelets have been employed in 
    multiwavelet polarization analysis, see Olhede and Walden (2003a,b).
 
    Again either bandpass or energy normalization can be applied.  With
    bandpass normalization, all wavelets are divided by a constant, setting
    the peak value of the first frequency-domain wavelet equal to 2.
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    The zero beta 
 
    For BETA equal to zero, the generalized Morse wavelets describe
    a non-zero-mean function which is not in fact a wavelet. 
 
    Only 'bandpass' normalization is supported for this case.
 
    In this case the input frequency speficies the half-power point of the
    analytic lowpass filter.  
 
    The frequency-domain definition of MORSEWAVE is not necessarily 
    a good way to compute the zero-beta functions, however.  You will
    probably need to take a very small DT.
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    Background
 
    For further details on generalized Morse wavelets, see the following 
    publications. 
 
      Lilly and Olhede (2012), Generalized Morse wavelets as a superfamily
         of analytic wavelets. IEEE Trans. Sig. Proc., 60 (11), 6036--6041.
 
      Lilly and Olhede (2009),  Higher-order properties of analytic 
          wavelets.  IEEE Trans. Sig. Proc., 57 (1), 146--160.
 
      Olhede and Walden (2002),  Generalized Morse Wavelets. IEEE Trans.
          Sig. Proc., 50 (11), 2661--2670.
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    'morsewave --t' runs a test.
    'morsewave --f' generates some sample figures.
 
    Usage: psi=morsewave(N,ga,be,fs);
           [psi,psif]=morsewave(N,ga,be,fs,'bandpass');
           [psi,psif]=morsewave(N,K,ga,be,fs,'energy');
           [psi,psif]=morsewave(N,K,ga,be,fs,'bandpass');
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    This is part of JLAB --- type 'help jlab' for more information
    (C) 2004--2016 J.M. Lilly and F. Rekibi
                          --- type 'help jlab_license' for details

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