A study of sudden noise resistance based on four-layer feed-forward neural network blind equalization algorithm

Authors:
Yanqi Kang;Liyi Zhang
Affiliations:
College of Mining Engineering, Taiyuan University of Technology, Taiyuan Shanxi, China;College of Information Engineering, Tianjin University of Commerce, Tianjin, China
Venue:
AICI'11 Proceedings of the Third international conference on Artificial intelligence and computational intelligence - Volume Part III
Year:
2011

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Nonlinear blind equalization schemes using complex-valued multilayer feedforward neural networks

IEEE Transactions on Neural Networks

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Abstract

In the study of feed-forward neural network blind equalization algorithm, three-layer BP neural network structure is usually adopted .In this paper, iterative formula of four-layer feed forward neural network blind equalization algorithm was deduced by way of adding hidden layers and computer simulations of its properties on sudden noise resistance were done. The experimental results demonstrate that three-layer and four-layer neural network have similar inhibitory action and the fault tolerance to the sudden noise, but four-layer neural network surpasses three-layer in steady-state residual error aspect.