Additive Gaussian noise channel ππ = π΄ + ππ for π = 1,2,....,1000 where ππ's are i.i.d. zero mean Gaussian random variables with variance π, i.e. ππ~π©(0, π). The signal π΄, and the noises ππ βs are independent.
The maximum likelihood estimate of the variance π using the first N samples where π β {10,100,1000}. For each case, calculate the absolute error between the estimated and the true value of π, i.e. |π β ππ‘ππ’π| where ππ‘ππ’π = "0.25".
Maximum-a-posteriori (MAP) estimator of π using the following scale inverse chisquare prior. MAP estimates of π using the first N samples, where π β {10,100,1000}. Setting the prior parameters such that Tao = 0.25 and v = 100.
