Simulation Line Design and Its FPGA Realization Based on BP Neural Network

Zhang Hai-yan; Li Xin; Tian Shu-feng

doi:10.3724/SP.J.1146.2005.01447

Volume 29 Issue 5

Jan. 2011

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Zhang Hai-yan, Li Xin, Tian Shu-feng . Simulation Line Design and Its FPGA Realization Based on BP Neural Network[J]. Journal of Electronics & Information Technology, 2007, 29(5): 1267-1270. doi: 10.3724/SP.J.1146.2005.01447

Citation:

Zhang Hai-yan, Li Xin, Tian Shu-feng . Simulation Line Design and Its FPGA Realization Based on BP Neural Network[J]. Journal of Electronics & Information Technology, 2007, 29(5): 1267-1270. doi: 10.3724/SP.J.1146.2005.01447

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Simulation Line Design and Its FPGA Realization Based on BP Neural Network

doi: 10.3724/SP.J.1146.2005.01447

Received Date: 2005-11-15
Rev Recd Date: 2006-10-26
Publish Date: 2007-05-19

Abstract

Abstract

A new method for simulation line realization based on Back Propagation Neural Network (BP NN) is presented in the paper. Applying Genetic Algorithm (GA) to optimize the neural networks structure, BP NN is trained to correspond the transfer function of simulation line. Activation function of NN is approximated with STAM (Symmetric Table and Addition Method) algorithms. A coaxial-cable which is 10000m long and 55 line characteristic impedance is simulated and realized by using FPGA and D/A converter. Experimental results show that the proposed approach can greatly reduce the memory of hardware realization. This method can be generalized to simulate the transmission network with unknown transfer function.

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References(1)

References

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