Adaptive non-linear network filter estimation error for stereo echo cancellation in home theatre 9.1 surround sound system

Abstract

In this paper, an adaptive non-linear network filter (ANLNF) approach based on Radial Basis Function Neural Networks (RBFNNs) is proposed for the stereo echo cancellation that is a necessary process for reducing undesired signal owing that the audiences can receive the apparent sound signal. The Gaussian activation function is suitable in used to model the characteristic of room transfer function. The samples of the direct sound and the echo sound signal in home theatre are applied as the input for the adaptive non-linear network filter. Finally, the simulation results illustrate the predicted error between the actual sound and direct sound, the Echo Return Loss Enhancement (ERLE) and Mean Square Error (MSE) in order to guarantee the clarity sound signal. We observe that the proposed algorithm outperforms compared with the other methods as Adaptive Filter with Gain and Time-Shift, Wiener Adaptive Filter, Feedforward Network and Average Recursive Least Square, respectively. © 2018, Int. J. of GEOMATE.