how NWIN and NOVERALP works in specgram.m from Matlab 6.5.

[emeipang]

Hi everyone,

I am using specgram to generate spectrum in time domain for visual analysis on audio signals. It will have good and clear visual effects while using NWINDOWS (128 PTS FROM HANNING), NOVERLAP = 100PTS UNDER 512 PTS FFT.

Questions to me as I want to implement the same overlap with windowing in my c source code:

I don't understand how the overlap works in specgram.m below.

Especially, these lines: (e.g., nwind = 129,ncol=6570)

y = zeros(nwind,ncol);

% put x into columns of y with the proper offset
% should be able to do this with fancy indexing!
y) = x(rowindex,ones(1,ncol))+colindex(ones(nwind,1),-1);

% Apply the window to the array of offset signal segments.
y = window,ones(1,ncol)).*y;

Thanks a lot for anyone's prompt reply. Greatly appreciated.


********* specgram.m from Matlab 6.5 **********
function [yo,fo,to] = specgram(varargin)
%SPECGRAM Calculate spectrogram from signal.
% B = SPECGRAM(A,NFFT,Fs,WINDOW,NOVERLAP) calculates the spectrogram for
% the signal in vector A. SPECGRAM splits the signal into overlapping
% segments, windows each with the WINDOW vector and forms the columns of
% B with their zero-padded, length NFFT discrete Fourier transforms. Thus
% each column of B contains an estimate of the short-term, time-localized
% frequency content of the signal A. Time increases linearly across the
% columns of B, from left to right. Frequency increases linearly down
% the rows, starting at 0. If A is a length NX complex signal, B is a
% complex matrix with NFFT rows and
% k = fix((NX-NOVERLAP)/(length(WINDOW)-NOVERLAP))
% columns. If A is real, B still has k columns but the higher frequency
% components are truncated (because they are redundant); in that case,
% SPECGRAM returns B with NFFT/2+1 rows for NFFT even and (NFFT+1)/2 rows
% for NFFT odd. If you specify a scalar for WINDOW, SPECGRAM uses a
% Hanning window of that length. WINDOW must have length smaller than
% or equal to NFFT and greater than NOVERLAP. NOVERLAP is the number of
% samples the sections of A overlap. Fs is the sampling frequency
% which does not effect the spectrogram but is used for scaling plots.
%
% [B,F,T] = SPECGRAM(A,NFFT,Fs,WINDOW,NOVERLAP) returns a column of
% frequencies F and one of times T at which the spectrogram is computed.
% F has length equal to the number of rows of B, T has length k. If you
% leave Fs unspecified, SPECGRAM assumes a default of 2 Hz.
%
% B = SPECGRAM(A) produces the spectrogram of the signal A using default
% settings; the defaults are NFFT = minimum of 256 and the length of A, a
% Hanning window of length NFFT, and NOVERLAP = length(WINDOW)/2. You
% can tell SPECGRAM to use the default for any parameter by leaving it
% off or using [] for that parameter, e.g. SPECGRAM(A,[],1000)
%
% SPECGRAM with no output arguments plots the absolute value of the
% spectrogram in the current figure, using IMAGESC(T,F,20*log10(ABS(B))),
% AXIS XY, COLORMAP(JET) so the low frequency content of the first
% portion of the signal is displayed in the lower left corner of the axes.
%
% SPECGRAM(A,F,Fs,WINDOW) where F is a vector of frequencies in Hz
% (with 2 or more elements) computes the spectrogram at those frequencies
% using either the chirp z-transform for more than 20 evenly spaced
% frequencies or a polyphase decimation filterbank.
%
% See also PWELCH, CSD, COHERE and TFE.

% Author(s): L. Shure, 1-1-91
% T. Krauss, 4-2-93, updated
% Copyright 1988-2002 The MathWorks, Inc.
% $Revision: 1.8 $ $Date: 2002/03/28 17:30:53 $

error(nargchk(1,5,nargin))
[msg,x,nfft,Fs,window,noverlap]=specgramchk(varargin);
error(msg)

nx = length(x);
nwind = length(window);
if nx < nwind % zero-pad x if it has length less than the window length
x(nwind)=0; nx=nwind;
end
x = x); % make a column vector for ease later
window = window); % be consistent with data set

ncol = fix((nx-noverlap)/(nwind-noverlap));
colindex = 1 + (0ncol-1))*(nwind-noverlap);
rowindex = (1:nwind)';
if length(x)<(nwind+colindex(ncol)-1)
x(nwind+colindex(ncol)-1) = 0; % zero-pad x
end

if length(nfft)>1
df = diff(nfft);
evenly_spaced = all(abs(df-df(1))/Fs<1e-12); % evenly spaced flag (boolean)
use_chirp = evenly_spaced & (length(nfft)>20);
else
evenly_spaced = 1;
use_chirp = 0;
end

if (length(nfft)==1) | use_chirp
y = zeros(nwind,ncol);

% put x into columns of y with the proper offset
% should be able to do this with fancy indexing!
y) = x(rowindex,ones(1,ncol))+colindex(ones(nwind,1),-1);

% Apply the window to the array of offset signal segments.
y = window,ones(1,ncol)).*y;

if ~use_chirp % USE FFT
% now fft y which does the columns
y = fft(y,nfft);
if ~any(any(imag(x))) % x purely real
if rem(nfft,2), % nfft odd
select = [1nfft+1)/2];
else
select = [1:nfft/2+1];
end
y = y(select,;
else
select = 1:nfft;
end
f = (select - 1)'*Fs/nfft;
else % USE CHIRP Z TRANSFORM
f = nfft);
f1 = f(1);
f2 = f(end);
m = length(f);
w = exp(-j*2*pi*(f2-f1)/(m*Fs));
a = exp(j*2*pi*f1/Fs);
y = czt(y,m,w,a);
end
else % evaluate DFT on given set of frequencies
f = nfft);
q = nwind - noverlap;
extras = floor(nwind/q);
x = [zeros(q-rem(nwind,q)+1,1); x];
% create windowed DTFT matrix (filter bank)
D = window,ones(1,length(f))).*exp((-j*2*pi/Fs*((nwind-1):-1:0)).'*f');
y = upfirdn(x,D,1,q).';
y,[1:extras+1 end-extras+1:end]) = [];
end

t = (colindex-1)'/Fs;

% take abs, and use image to display results
if nargout == 0
newplot;
if length(t)==1
imagesc([0 1/f(2)],f,20*log10(abs+eps));axis xy; colormap(jet)
else
imagesc(t,f,20*log10(abs+eps));axis xy; colormap(jet)
end
xlabel('Time')
ylabel('Frequency')
elseif nargout == 1,
yo = y;
elseif nargout == 2,
yo = y;
fo = f;
elseif nargout == 3,
yo = y;
fo = f;
to = t;
end

function [msg,x,nfft,Fs,window,noverlap] = specgramchk(P)
%SPECGRAMCHK Helper function for SPECGRAM.
% SPECGRAMCHK(P) takes the cell array P and uses each cell as
% an input argument. Assumes P has between 1 and 5 elements.

msg = [];

x = P{1};
if (length(P) > 1) & ~isempty(P{2})
nfft = P{2};
else
nfft = min(length(x),256);
end
if (length(P) > 2) & ~isempty(P{3})
Fs = P{3};
else
Fs = 2;
end
if length(P) > 3 & ~isempty(P{4})
window = P{4};
else
if length(nfft) == 1
window = hanning(nfft);
else
msg = 'You must specify a window function.';
end
end
if length(window) == 1, window = hanning(window); end
if (length(P) > 4) & ~isempty(P{5})
noverlap = P{5};
else
noverlap = ceil(length(window)/2);
end

% NOW do error checking
if (length(nfft)==1) & (nfft<length(window)),
msg = 'Requires window''s length to be no greater than the FFT length.';
end
if (noverlap >= length(window)),
msg = 'Requires NOVERLAP to be strictly less than the window length.';
end
if (length(nfft)==1) & (nfft ~= abs(round(nfft)))
msg = 'Requires positive integer values for NFFT.';
end
if (noverlap ~= abs(round(noverlap))),
msg = 'Requires positive integer value for NOVERLAP.';
end
if min(size(x))~=1,
msg = 'Requires vector (either row or column) input.';
end

 

[GregLocock]

Overlap % is how much each frame of data is shared with the previous frame.

So for a 128 pt fft with 75% overlap the first fft would be of datapoints 1-128, the second 32-159, and so on.



Cheers

Greg Locock


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