Adaptive Noise Cancellation Using Petri Fuzzy Brain Emotional Learning-Based Neural Network

Abstract

This study briefs the application of a novel intelligent algorithm as an adaptive filter. The proposed algorithm, Petri fuzzy brain emotional learning-based neural network (PNFBELNN) is designed by introducing Petri Net layers in fuzzy brain emotional learning-based neural network. The Petri Net reduces the computational load caused by parameter learning and improves fuzzy reasoning thus enabling high-speed signal processing. The proposed filter is applied as an adaptive noise canceller. The performance of the filter is illustrated through numerical simulations of the noise cancelation system.