3.1 OPTIMUM SOLUTION
In this case, the theory starts with a simple problem where, for a received signal r(t) = s(t, θ ) + n(t), we have to estimate a generalized time invariant vector of parameters θ (frequency, phase, delay, data, . . .) of a signal s(t, θ ) in the presence of Gaussian noise ˆ n(t). The best that we can do is to ﬁnd an estimate θ of the parameter θ for which ˆ /r) is maximum; hence the name maximum aposterior the aposterior probability p(θ probability (MAP) estimate. In other words, the chosen estimate based on...