A solution to linear estimation problems using approximate Karhunen-Loeve expansions

An explicit and efficiently calculable solution is presented to the problem of linear least-mean-squared-error estimation of a signal process based upon noisy observations that is valid for finite intervals. This approach is based on approximate Karhunen-Loeve expansions of a stochastic process and can be extended to estimate a linear operation, in the sense of the quadratic mean, of the signal process