DocumentCode :
527501
Title :
Blind multi-valued signals detection using discrete Hopfield network
Author :
Zhang, Yun ; Zhang, Zhi-Yong
Author_Institution :
Coll. of Telecommun. & Inf. Eng., Nanjing Univ. of Posts & Telecommun., Nanjing, China
Volume :
2
fYear :
2010
fDate :
10-12 Aug. 2010
Firstpage :
1079
Lastpage :
1083
Abstract :
The conventional neural networks which are limited to two-state neurons are not able to solve the problem of blind multi-valued signal detection. A new algorithm based on discrete Hopfield neural network(DHNN) is proposed to detect multivalued signals blindly. A discrete 4-level signum-type activation function is constructed for 4PAM signals. For the blind signal detection, the optimization performance function is constructed and it does not rely on the second or higher order statistics of the received signals. Based on the new weight matrixes and the energy function of multi-value DHNN, the stability for multi-value DHNN is also proved in the paper. Simulation results show that the algorithm reach the real equilibrium points in a few iterations and show high speed to blindly detect multi-valued signals in stochastic channels.
Keywords :
Hopfield neural nets; blind source separation; iterative methods; matrix algebra; signal detection; stochastic processes; blind multivalued signals detection; discrete 4-level signum-type activation function; discrete Hopfield neural network; energy function; neural networks; optimization performance function; stochastic channels; weight matrix; Artificial neural networks; Bit error rate; Hopfield neural networks; Neurons; Signal detection; Signal to noise ratio; Simulation; Discrete hopfield neural network(DHNN); Multi-valued signals; blind detection;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Natural Computation (ICNC), 2010 Sixth International Conference on
Conference_Location :
Yantai, Shandong
Print_ISBN :
978-1-4244-5958-2
Type :
conf
DOI :
10.1109/ICNC.2010.5583004
Filename :
5583004
Link To Document :
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