ADAPTIVE NON-LINEAR NETWORK FILTER ESTIMATION ERROR FOR STEREO ECHO CANCELLATION IN HOME THEATRE 9.1 SURROUND SOUND SYSTEM

Authors

  • Sunisa Kunarak

Keywords:

Adaptive Non-Linear Network Filter, Echo Return Loss Enhancement,, Mean Square Error, Radial Basis Function Neural Networks, Stereo Echo Cancellation

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.

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Published

2018-01-15

How to Cite

Sunisa Kunarak. (2018). ADAPTIVE NON-LINEAR NETWORK FILTER ESTIMATION ERROR FOR STEREO ECHO CANCELLATION IN HOME THEATRE 9.1 SURROUND SOUND SYSTEM . GEOMATE Journal, 15(49), 17–22. Retrieved from https://geomatejournal.com/geomate/article/view/928