wnoise (Wavelet Toolbox)

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 2^N 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'

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.

See Also
wden

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.

wmaxlev wnoisest