A Novel Fully Complex Nonlinear Adaptive Finite Impulse Response Filter Algorithm

Abstract

In this study, a new fully complex nonlinear adaptive finite impulse response (FIR) filter algorithm based on the complex-valued nonlinear least mean kurtosis (CNLMK) is proposed for nonlinear complex-valued signals. The performance of the proposed nonlinear adaptive FIR filter algorithm is assessed on the prediction of complex-valued signals. In addition, the performance of the proposed algorithm is compared with the complex-valued nonlinear gradient descent (CNGD) algorithm in terms of the mean square error (MSE) and the prediction gain. Simulation results clearly demonstrate that the proposed CNLMK algorithm outperforms the CNGD algorithm.

Keywords

• FIR filter CNLMK algorithm Prediction
• Complex-valued signals
• FIR filter CNLMK algorithm
• Prediction
• FIR filter
• CNLMK algorithm