Removable Noise from SOS Nonlinear System using Adaptive Second Order LMS Volterra Series Filter

Nature of much process in industry is nonlinear. Every process of system suffered with unwanted signals called noise, if this noise randomly generated in desire system output than normal or linear filter are fail to remove it kind of noise from desire signal. This paper proposes an Adaptive Second Order Volterra Series Filter (ASVSF) for reducing noise from nonlinear system. Based on the lattice-channel structure with delayed element, updates kernel parameters. In order to reduce the computational complexity and the nonlinear distortion with no need of solving the lengthy second order nonlinear mathematics acoustic equation, the ASVSF-LMS filter is proposed. MATLAB simulations demonstrate the control performance improvement using the proposed algorithms.