LAUSR

To lower the high computational burden of nonlinear filter in the practical applications, the previous paper has proposed the adaptive algorithm based on the joint process filter using pipelined feedforward second-order Volterra architecture (JPPSOV). Even though the JPPSOV adaptive filter has been common used for nonlinear systems identification, nonlinear active noise controller (ANC) and nonlinear acoustic echo cancellers (AEC), there is currently no literature that gives the steady state analysis of JPPSOV. Therefore, we analyze the steady state performance of the LMS adaptive algorithm of the JPPSOV filter for nonlinear system identification in this brief. Finally, the simulated results are in good agreement with the theoretical results.