kopia lustrzana https://github.com/ag1le/morse-wip
77 wiersze
2.7 KiB
Matlab
77 wiersze
2.7 KiB
Matlab
function [ noisy, noise ] = addnoise( signal, noise, snr )
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% ADDNOISE Add noise to signal at a prescribed SNR level.
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%
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% [NOISY,NOISE]=ADDNOISE(SIGNAL,NOISE,SNR) adds NOISE to SIGNAL
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% at a prescribed SNR level. Returns the mixture signal as well
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% as scaled noise such that NOISY=SIGNAL+NOISE.
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%
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% Inputs
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% SIGNAL is a target signal as vector.
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%
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% NOISE is a masker signal as vector, such that
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% length(NOISE)>=length(SIGNAL). Note that
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% in the case that length(NOISE)>length(SIGNAL),
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% a vector of length length(SIGNAL) is selected
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% from NOISE starting at a random sample number.
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%
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% SNR is the desired signal-to-noise ratio level (dB).
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%
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% Outputs
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% NOISY is a mixture signal of SIGNAL and NOISE at given SNR.
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%
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% NOISE is a scaled masker signal, such that the mixture
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% NOISY=SIGNAL+NOISE has the desired SNR.
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%
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% Example
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% % inline function for SNR calculation
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% SNR = @(signal,noisy)( 20*log10(norm(signal)/norm(signal-noisy)) );
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%
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% fs = 16000; % sampling frequency (Hz)
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% freq = 1000; % sinusoid frequency (Hz)
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% time = [ 0:1/fs:2 ]; % time vector (s)
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% signal = sin( 2*pi*freq*time ); % signal vector (s)
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% noise = randn( size(signal) ); % noise vector (s)
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% snr = -5; % desired SNR level (dB)
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%
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% % generate mixture signal: noisy = signal + noise
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% [ noisy, noise ] = addnoise( signal, noise, snr );
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%
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% % check the resulting signal-to-noise ratio
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% fprintf( 'SNR: %0.2f dB\n', SNR(signal,noisy) );
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%
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% See also TEST_ADDNOISE_SINUSOID, TEST_ADDNOISE_SPEECH.
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% Author: Kamil Wojcicki, UTD, July 2011
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% inline function for SNR calculation
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SNR = @(signal,noisy)( 20*log10(norm(signal)/norm(signal-noisy)) );
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% needed for older realases of MATLAB
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randi = @(n)( round(1+(n-1)*rand) );
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% ensure masker is at least as long as the target
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S = length( signal );
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N = length( noise );
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if( S>N ), error( 'Error: length(signal)>length(noise)' ); end;
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% generate a random start location in the masker signal
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R = randi(1+N-S);
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% extract random section of the masker signal
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noise = noise(R:R+S-1);
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% scale the masker w.r.t. to target at a desired SNR level
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noise = noise / norm(noise) * norm(signal) / 10.0^(0.05*snr);
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% generate the mixture signal
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noisy = signal + noise;
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% plot(signal,noisy,noise);
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% sanity check
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%assert( abs(SNR(signal,noisy)-snr) < 1E10*eps(snr) );
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%%% EOF
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