Documentation

This is machine translation

Translated by Microsoft
Mouse over text to see original. Click the button below to return to the English verison of the page.

wnoise

Noisy wavelet test data

Syntax

X = wnoise(FUN,N)
[X,XN] = wnoise(FUN,N,SQRT_SNR)
[X,XN] = wnoise(FUN,N,SQRT_SNR,INIT)

Description

X = wnoise(FUN,N) returns values of the test signal given by FUN, on a 2N grid of [0,1].

[X,XN] = wnoise(FUN,N,SQRT_SNR) returns a test vector X as above, rescaled such that std(X) = SQRT_SNR. The returned vector XN contains the same test vector corrupted by additive Gaussian white noise N(0,1). Then, XN has a signal-to-noise ratio of SNR = (SQRT_SNR)2.

[X,XN] = wnoise(FUN,N,SQRT_SNR,INIT) returns previous vectors X and XN, but the generator seed is set to INIT value.

The six functions below are due to Donoho and Johnstone (See "References").

FUN = 1     or'blocks'
FUN = 2     or'bumps'
FUN = 3     or'heavy sine'
FUN = 4     or'doppler'
FUN = 5     or'quadchirp'
FUN = 6     or'mishmash'

Examples

% Generate 2^10 samples of 'Heavy sine' (item 3). 
x = wnoise(3,10); 

% Generate 2^10 samples of 'Doppler' (item 4) and of
% noisy 'Doppler' with a square root of signal-to-noise
% ratio equal to 7. 
[x,noisyx] = wnoise(4,10,7);

% To introduce your own rand seed, a fourth 
% argument is allowed: 
init = 2055415866; 
[x,noisyx] = wnoise(4,10,7,init);

% Plot all the test functions. 
ind = linspace(0,1,2^10); 
for i = 1:6 
    x = wnoise(i,10); 
    subplot(6,1,i), plot(ind,x) 
end

% Editing some graphical properties,
% the following figure is generated.

References

Donoho, D.L.; I.M. Johnstone (1994), "Ideal spatial adaptation by wavelet shrinkage," Biometrika, vol. 81, pp. 425–455.

Donoho, D.L.; I.M. Johnstone (1995), "Adapting to unknown smoothness via wavelet shrinkage via wavelet shrinkage," JASA, vol. 90, 432, pp. 1200–1224.

See Also

Introduced before R2006a

Was this topic helpful?