📄 bispec.m
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function [BISPEC,BIACF,ACF] = bispec(Z,N);
% Calculates Bispectrum
% [BISPEC] = bispec(Z,N);
%
% Input: Z Signal
% N # of coefficients
% Output: BiACF bi-autocorrelation function = 3rd order cumulant
% BISPEC Bi-spectrum
%
% Reference: M.B. Priestley (1988) Non-linear and Non-stationary Time series Analysis
% Version 2.30
% last revision 21.03.1998
% Copyright (c) 1997, 1998 by Alois Schloegl
% e-mail: a.schloegl@ieee.org
% This library is free software; you can redistribute it and/or
% modify it under the terms of the GNU Library General Public
% License as published by the Free Software Foundation; either
% version 2 of the License, or (at your option) any later version.
%
% This library is distributed in the hope that it will be useful,
% but WITHOUT ANY WARRANTY; without even the implied warranty of
% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
% Library General Public License for more details.
%
% You should have received a copy of the GNU Library General Public
% License along with this library; if not, write to the
% Free Software Foundation, Inc., 59 Temple Place - Suite 330,
% Boston, MA 02111-1307, USA.
P=N+1;
ACF=zeros(1,N+1);
BIACF=zeros(2*N+1,2*N+1);
Z=Z(:);
M=size(Z,1);
M1=sum(Z)/M;
Z=Z-M1*ones(size(Z));
for K=0:N,
jc2=Z(1:M-K).*Z(1+K:M);
ACF(K+1)=sum(jc2)/M;
for L = K:N,
jc3 = sum(jc2(1:M-L).*Z(1+L:M))/M;
BIACF(K+P, L+P) =jc3;
BIACF(L+P, K+P) =jc3;
BIACF(L-K+P, -K+P)=jc3;
BIACF(-K+P, L-K+P)=jc3;
BIACF(K-L+P, -L+P)=jc3;
BIACF(-L+P, K-L+P)=jc3;
end;
end;
BISPEC=fft2(BIACF,128,128);
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