Question: ML Estimation with correlated noises. A parameter r is measured with correlated rather than independent additive Gaussian noises zk = x + wk k =

ML Estimation with correlated noises. A parameter r is measured with

ML Estimation with correlated noises. A parameter r is measured with correlated rather than independent additive Gaussian noises zk = x + wk k = 1,...,n 0 with 1 k=j E(W) = 0 E[WkW;] = lk-il = 1 |k-j> 1 For n = 2: 1. Write the likelihood function of the parameter 1. 2. Find the MLE of r. What happens if p = 1? What happens if p=-1? 3. Find the CRLB for the estimation of r. Show the effect of p > 0 versus p 1 For n = 2: 1. Write the likelihood function of the parameter 1. 2. Find the MLE of r. What happens if p = 1? What happens if p=-1? 3. Find the CRLB for the estimation of r. Show the effect of p > 0 versus p

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