Title :
On a class of random processes exhibiting optimal nonlinear one-step predictors (Corresp.)
Author :
Mccannon, T.E. ; Gallagher, Neal C.
fDate :
9/1/1981 12:00:00 AM
Abstract :
Two classes of random processes that exhibit one-step predictors with optimal nonlinear minimum mean-squared error (MMSE) are discussed, and conditions for membership to one of these classes are given. Examples of each class are presented, and the optimal one-step predictors are given.
Keywords :
Nonlinear estimation; Prediction methods; Stochastic processes; Design methodology; Information filtering; Information filters; Nonlinear equations; Nonlinear filters; Polynomials; Random processes; Random variables; Sampling methods; Writing;
Journal_Title :
Information Theory, IEEE Transactions on
DOI :
10.1109/TIT.1981.1056395
