NONLINEAR ADAPTIVE FILTER PERFORMANCE IN TYPICAL APPLICATIONS

This paper examines approaches to the realisation of nonlinear filters as used in signal and image processing. The design of adaptive nonlinear processors is examined and their application as adaptive equalisers to alleviate bandlimiting, distortion and interference in a typical communications channel is investigated. This paper re-examines the equalisation process as one which seeks to correctly classify the channel output into one of a finite and known alphabet of symbols encompassing the data at the channel input. The optimal solution for this classification problem is shown to be inherently nonlinear. Several nonlinear structures are examined, which allow much more complex classification boundaries, and provide greatly enhanced performance for the nonlinear filter over the more conventional linear filter. Finally the use of a nonlinear predictor is investigated for time series analysis.

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