Communication systems engineering
Communication systems engineering
Equalization of 8PSK Signals with a Recurrent Neural Network
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III
Equalization for a Wireless ATM Channel with a Recurrent Neural Network Pruned by Genetic Algorithm
SNPD '08 Proceedings of the 2008 Ninth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing
Equalization of 16 QAM signals with reduced bilinear recurrent neural network
IEA/AIE'07 Proceedings of the 20th international conference on Industrial, engineering, and other applications of applied intelligent systems
On the convergence of Volterra filter equalizers using a pth-orderinverse approach
IEEE Transactions on Signal Processing
IEEE Journal on Selected Areas in Communications
Volterra models and three-layer perceptrons
IEEE Transactions on Neural Networks
Nonlinear blind equalization schemes using complex-valued multilayer feedforward neural networks
IEEE Transactions on Neural Networks
Complex-bilinear recurrent neural network for equalization of a digital satellite channel
IEEE Transactions on Neural Networks
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A equalisation method of a wireless Asynchronous Transfer Mode (ATM) communication channel using a Complex BiLinear Recurrent Neural Network (CBLRNN) is proposed in this paper. A Genetic Algorithm (GA) is used for the pruning process of the trained CBLRNN. As a result, a pruned Bilinear Recurrent Neural Network (BLRNN) is obtained and the pruned BLRNN can reduce the computational cost by 29.9% in terms of the number of weights. The equaliser based on CBLRNN pruned by the GA is compared with Decision Feedback Equaliser (DFE), Volterra filter based equaliser, and Multilayer Perceptron Neural Network Equaliser. Experiments show that the pruned CBLRNN equaliser for 8PSK signals gives favourable results in the Symbol Error Rate (SER) criterion over conventional equalisers.