Abstract
A Chebyshev polynomial expansion based functional link adaptive filter is introduced for the identification of nonlinear sparse system with the interference of impulsive noise environment in this manuscript. Most of the functional link adaptive filters used to identify the unknown nonlinear systems have high computational load, slow convergence speed and also poor robustness to the impulsive noise. Hence to minimize the computational load and increase the robustness against impulsive noise in nonlinear systems, recursive Chebyshev functional link adaptive filter (R-CFLAF) has been proposed. Simulation results show fast rate of convergence and enhanced the steady state performance of R-CFLAFs in the event of impulsive noise contamination for nonlinear systems.
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