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Matlab for Welch's Method

Octave and the Matlab Signal Processing Toolbox have a pwelch function. Note that these functions also provide confidence intervals (not covered here). Matlab for generating the data shown in Fig.6.1 (employing Welch's method) appears in Fig.6.2.

Figure: Matlab listing for generating data plotted in Fig.6.1.

M = 32;
Ks=[1 8 32 128]
nkases = length(Ks);
for kase = 1:4
  K = Ks(kase);
  N = M*K;
  Nfft = 2*M; % zero pad for acyclic autocorrelation
  Sv = zeros(Nfft,1); % PSD "accumulator"
  for m=1:K
    v = randn(M,1);  % noise sample
    V = fft(v,Nfft);
    Vms = abs(V).^2; % same as conj(V) .* V
    Sv = Sv + Vms;   % sum scaled periodograms
  Sv = Sv/K;     % average of all scaled periodograms
  rv = ifft(Sv); % Average Bartlett-windowed sample autocor.
  rvup = [rv(Nfft-M+1:Nfft)',rv(1:M)']; % unpack FFT
  rvup = rvup/M; % Normalize for no bias at lag 0

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