📄 binomial2.m
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function [tfd, t, f] = binomial2(x, fs, nfreq, wlen)% binomial2 -- Compute samples of the type II binomial distribution.%% Usage% [tfd, t, f] = binomial2(x, fs, nfreq, wlen)%% Inputs% x signal vector% fs sampling frequency of x (optional, default is 1 sample/second)% nfreq number of samples to compute in frequency (optional, default% is twice the length of x)% wlen length of the rectangular lag window on the auto-correlation% function, must be less than or equal to nfreq (optional, default% is twice the length of x)%% Outputs% tfd matrix containing the binomial distribution of signal x. If x has% length N, then tfd will be nfreq by N. (optional)% t vector of sampling times (optional)% f vector of frequency values (optional)%% If no output arguments are specified, then the binomial distribution is % displayed using ptfd(tfd, t, f).% Copyright (C) -- see DiscreteTFDs/Copyright% specify defaultsx = x(:);N = length(x);error(nargchk(1, 4, nargin));if (nargin < 4) wlen = 2*N;endif (nargin < 3) nfreq = 2*N;endif (nargin < 2) fs = 1;endif (nfreq < wlen) error('wlen must be less than or equal to nfreq!');endif (wlen > 2*N) error('wlen must be less than or equal to twice the length of the signal!');endw = wlen/2;% make the binomial kernel%%%%%%%%%%%%%%%%%%%%%%%%%%%%ker = zeros(w);ker(1,1) = 1;for tau = 2:w, temp = ker(tau-1,1:tau-1); ker(tau,1:tau) = ([0 temp] + [temp 0])/2;end% Do the computations.%%%%%%%%%%%%%%%%%%%%%%% make the acf for positive tauacf = lacf2(x, w);% convolve with the kernelacf2 = fft(acf.');ker = [ker zeros(w,N-w)];ker2 = fft(ker.');gacf = ifft(acf2.*ker2);gacf = gacf.';% make the gacf for negative lagsgacf = [gacf ; zeros(nfreq-wlen+1,N) ; conj(flipud(gacf(2:w,:)))];%compute the tfdtfd = real(fft(gacf));tfd = tfdshift(tfd)/nfreq;t = 1/fs * (0:N-1);f = -fs/2:fs/nfreq:fs/2;f = f(1:nfreq);if (nargout == 0) ptfd(tfd, t, f); clear tfdend
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