文件名称:Lab4-LPC
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For restoration of time-domain signals, an
estimate of the instantaneous magnitude spectrum is combined with the
phase of the noisy signal, and then transformed via an inverse discrete
Fourier transform to the time domain. In terms of computational
complexity, spectral subtraction is relatively inexpensive. However, owing
to random variations of noise, spectral subtraction can result in negative
estimates of the short-time magnitude or power spectrum-For restoration of time-domain signals, an
estimate of the instantaneous magnitude spectrum is combined with the
phase of the noisy signal, and then transformed via an inverse discrete
Fourier transform to the time domain. In terms of computational
complexity, spectral subtraction is relatively inexpensive. However, owing
to random variations of noise, spectral subtraction can result in negative
estimates of the short-time magnitude or power spectrum
estimate of the instantaneous magnitude spectrum is combined with the
phase of the noisy signal, and then transformed via an inverse discrete
Fourier transform to the time domain. In terms of computational
complexity, spectral subtraction is relatively inexpensive. However, owing
to random variations of noise, spectral subtraction can result in negative
estimates of the short-time magnitude or power spectrum-For restoration of time-domain signals, an
estimate of the instantaneous magnitude spectrum is combined with the
phase of the noisy signal, and then transformed via an inverse discrete
Fourier transform to the time domain. In terms of computational
complexity, spectral subtraction is relatively inexpensive. However, owing
to random variations of noise, spectral subtraction can result in negative
estimates of the short-time magnitude or power spectrum
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下载文件列表
sp01VN.mat
lpcAR.m