Adaptive linearization schemes for weakly nonlinear systems using adaptive linear and nonlinear FIR filters

Three adaptive linearization schemes are proposed. In the first scheme, linearization is performed by canceling nonlinearity at the output of a physical system. In the second, a nonlinear postprocessor is employed to postdistort signals. In the third, a preprocessor is used. The schemes using a postprocessor and a preprocessor are designed for weakly nonlinear systems, whereas the scheme of linearization by cancellation at the output can be applied to problems with stronger nonlinearities. In all three methods, necessary estimates of linear and nonlinear operators are provided by adaptive linear and nonlinear filters. Typical simulation results for a physical system modeled by a Volterra series with a linear term, a quadratic term, and a cubic term are presented and are judged encouraging