A novel hysteretic noisy chaotic neural network and its application to TDMA broadcast scheduling

In order to enhance the optimization ability of hysteretic dynamics in the noisy chaotic neural network, and not to increase any parameters into the noisy chaotic neural network, this paper presents a novel hysteretic noisy chaotic neural network by taking noise amplitudes of the noisy chaotic neura...

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Bibliographic Details
Published in2012 5th International Conference on Biomedical Engineering and Informatics pp. 1411 - 1415
Main Authors Sun, Ming, Zhao, Yanjun, Cao, Wei, Li, Yandong
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2012
Subjects
Bifurcation
Biological neural networks
Chaotic communication
Hysteresis
Mathematical models
Neurons
Noise
noise chaotic neural network
Noise measurement
Optimization
Simulated annealing
TDMA broadcast scheduling
Time division multiple access
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ISBN9781467311830
1467311839
DOI10.1109/BMEI.2012.6513151

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Summary:In order to enhance the optimization ability of hysteretic dynamics in the noisy chaotic neural network, and not to increase any parameters into the noisy chaotic neural network, this paper presents a novel hysteretic noisy chaotic neural network by taking noise amplitudes of the noisy chaotic neural network as center parameters of Sigmoid function and using inputs' change of neurons to control noise amplitudes to form hysteretic loop. The proposed network can evolve dynamics including chaotic reverse bifurcation, stochastic wandering and hysteresis. Simulations in TDMA broadcast scheduling problem in packet radio networks suggest that the proposed hysteretic noisy chaotic neural network can behave better optimization performance.
ISBN:9781467311830
1467311839
DOI:10.1109/BMEI.2012.6513151