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´ó¼Ò°ïæ¿´¿´£¬ÎÒÉèµÄSNR=2,µ«ÊÇËæºóÓÃsnrs=20*log10(norm(x)/norm(s-x))¼ÆËãµÄÈ´Ïà²îºÜ´ó£¬ÊÇÔõô»ØÊ£¿¹«Ê½ÓôíÁË£¬»¹ÊÇÎÒ¶Ôwnoiseº¯ÊýÀí½âµÄ ÓÐÎÊÌ⣿ ¸½´úÂ룺 %²âÊÔÊý¾ÝµÄѡȡ snr =2; init = 2055615866; % Generate original signal and a noisy version adding % a standard Gaussian white noise. xref is the origin signal,and x % 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,signal] = wnoise(3,11,snr,init);%generate the signal containing 2^11 dots.,x is the origin singnal and signal is the noising signal. s=signal; N=2^11; wname='db7'; jN=6; %·Ö½âµÄ²ãÊý [c,l]=wavedec(s,jN,wname); snrs=20*log10(norm(x)/norm(s-x)); |
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[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. SNR, the ratio of signal power to noise power ×Ô¼º¶à²é²ématlabµÄ°ïÖú£¬ÄÇ¿ÉÊÇÒ»¸öÊýѧ°Ù¿ÆÈ«Êé |
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3Â¥2009-05-16 14:33:50
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4Â¥2009-05-17 15:47:56













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