An extended nonlinear transform domain adaptive filter

Abstract

The concept of nonlinear transform domain adaptive filtering is extended to handle general inputs. Two solutions are proposed and a local temporal relationship is established between them. Layered implementation is shown to achieve performance comparable to the linear embedding solution with considerably reduced computations. Computer simulation shows improved learning performance compared to the LMS based structure driven with a non-Gaussian input.<>