An approach to neuro-fuzzy filtering for communications and control

Abstract

To reduce the influence of noise in communication and control systems the use of neuro-fuzzy adaptive nonlinear filters is studied. The most important advantage of the soft computing based adaptive filters is that linguistic and numerical information can be efficiently combined. A unified procedure for filter design is presented, and different approaches are also considered.