## Biomedical Signal Processing: Time and frequency domains analysis, Volume 1Time and frequency domains analysis. |

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Acoust action potential adaptive filter adaptive noise canceller algorithm amplitude applications ARMA model Assume autocorrelation function biomedical signal Blackman-Tukey calculated cepstrum Chapter complex cepstrum computation Consider convolution correlation coefficients correlation function correlation matrix covariance defined denote difference equation discrete discussed estimator Equation example Figure finite Fourier transform frequency domain function estimation gaussian hence IEEE IEEE Trans impulse response input inverse joint probability LMS adaptive LMS filter maximum entropy mean square error membrane method minimization model order nonstationary output parameters periodogram Power spectral density probability density function problem Proc PSD estimation PSD function random process random signal random variable sample function sampled signal sequence Sj series analysis signal x(t signal-to-noise ratio sinusoids sliding window spectral analysis spectral estimation spectrum Speech Signal Process stationary process statistically independent techniques u(nT variance vector wavelet white noise Widrow x(nT yields