8.1. Assume x[n] is a second-order autoregressive process defined by the difference equation, x[n] = 1.2728x[n 1]
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8.1. Assume x[n] is a second-order autoregressive process defined by the difference equation, x[n] = 1.2728x[n −1] − 0.81x[n − 2]+ v[n] , where v[n] is unit variance white noise the optimum causal predictor for x[n] is given by, xˆ[n] = 1.2728x[n −1]− 0.81x[n − 2] .
Show how you could go about computing the predictor coefficients 1.2728 and -0.81 using the LMS algorithm.
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