混沌神经网络的动态阈值控制

张旭东; 朱萍; 谢小平; 何国光

doi:10.7498/aps.62.210506

摘要

提出了混沌神经网络的动态阈值控制方法, 将大脑脑电波的主要成分, 正弦信号作为控制变量实现对混沌神经网络内部状态的阈值动态改变, 从而达到了控制混沌神经网络混沌的目的. 利用该方法可以将混沌神经网络的输出稳定在一个与网络初始模式相关的存储模式和其反相模式上, 从而使混沌神经网络在模式识别、信息搜索等信息处理功能得以实现. 该控制方法不需要事先指定阈值, 是一种自适应方法, 符合实际人脑的思维运动.

关键词:

Abstract

A dynamic threshold value control method is proposed to get control over a chaotic neural network (CNN). The sinusoidal signal, which constitutes the key component of the brain wave, is taken as the control signal to change the threshold value of the internal states of the CNN. The chaos control of the CNN is therefore reached with its outputs of the controlled CNN reciprocating between a stored pattern and its reverse pattern related with the initial pattern. And then the CNN can be applied in information processing, such as pattern recognitionetc. The chaos control method works in a self-adaption way since it does not need to set the threshold value beforehand, which is in accordance with brains’ thinking activities.

Keywords:

作者及机构信息

1.
浙江大学物理学系, 杭州 310027

基金项目: 国家自然科学基金 (批准号: 61175060)和浙江大学物理学人才培养基地–科研训练及科研能力提高项目(批准号: J1210046)资助的课题.

Authors and contacts

1.
Department of Physics, Zhejiang University, Hangzhou 310027, China

Funds: Project supported by the National Natural Science Foundation of China (Grant No. 61175060), and the Research Training and Research Ability Enhancement in Physics Fostering Talents of Zhejiang University (Grant No. J1210046).

参考文献

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[5]	Pecora L M, Carroll T L 1990 Phys. Rev. Lett. 64 821
[6]	Huberman B A, Lumer E 1990 IEEE Trans. on Circuits Syst. 37 547
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[11]	L J H, Zhou T S, Zhang S C 2002 Chin. Phys. 11 12
[12]	Li L X, Peng H P, Lu H B 2001 Chin. Phys. 10 796
[13]	Li X L, Fu D X, Ma Y W 2006 Chin. Phys. Lett. 23 1519
[14]	Sang H B, He K F 2004 Chin. Phys. Lett. 21 254
[15]	Fahy S, Hamann D R 1992 Phys. Rev. Lett. 69 761
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[17]	Sang H B, He K F 2004 Chin. Phys. Lett. 21 254
[18]	Huang L Y, Luo X S 2006 Chin. Phys. Lett. 23 297
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[20]	He G, Chen L, Aihara K 2008 Neurocomputing 71 2794
[21]	He G, Shrimali M D, Aihara K 2007 Physics Letters A 371 228
[22]	He G, Shrimali M D, Aihara K 2008 Neural networks 21 114
[23]	He G G, Zhu P, Chen H P 2010 Acta Phys. Sin. 59 140 (in Chinese) [何国光, 朱萍, 陈宏平 2010 59 140]
[24]	He G, Cao Z, Chen H, Zhu P 2003 International Journal of Modern Physics B 17 4209
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[26]	Watanabe M, Aihara K, Kondo S 1996 Electron. Commun. Japan Part III 79 87
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[28]	Wang Z, Fan H, Aihara K 2007 Internat. J. Bifur. Chaos 17 3085
[29]	Li Y, Zhu P, Xie X, He G, Aihara K 2012 Phys. Lett. A 376 412
[30]	Sih G C, Tang K K 2012 Theoretical and Applied Fracture Mechanics 61 21
[31]	Freeman W J, Viana Di Prisco G 1986 Brain Theory (Berlin: Springer-Verlag) p97
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施引文献

[1]	Aihara K, Takabe T, Toyoda M 1990 Phys. Lett. A 144 333
[2]	Tokuda I, Nagashima T, Aihara K 1997 Neural Networks. 10 1673
[3]	Wang B Y, Nie J N, He Z Y 1999 IEEE Trans. on Neural Networks. 10 1257
[4]	Ott E, Grebogi C, Yorke J A 1990 Phys. Rev. Lett. 64 1196
[5]	Pecora L M, Carroll T L 1990 Phys. Rev. Lett. 64 821
[6]	Huberman B A, Lumer E 1990 IEEE Trans. on Circuits Syst. 37 547
[7]	Hunt E R 1991 Phys. Rev. Lett. 67 1953
[8]	Pyragas K, Tamasericius A 1992 Phys. Lett. A 170 421
[9]	Luo X S, Fang J Q, Kong L J 2000 Acta Phys. Sin. 49 1423 (in Chinese) [罗晓曙, 方锦清, 孔令江 2000 49 1423]
[10]	Chen S H, Liu J, Xie J 2002 Chin. Phys. 11 233
[11]	L J H, Zhou T S, Zhang S C 2002 Chin. Phys. 11 12
[12]	Li L X, Peng H P, Lu H B 2001 Chin. Phys. 10 796
[13]	Li X L, Fu D X, Ma Y W 2006 Chin. Phys. Lett. 23 1519
[14]	Sang H B, He K F 2004 Chin. Phys. Lett. 21 254
[15]	Fahy S, Hamann D R 1992 Phys. Rev. Lett. 69 761
[16]	Luo X S, Wang B H, Chen G R 2002 Acta Phys. Sin. 51 988 (in Chinese) [罗晓曙, 汪秉宏, 陈关荣 2002 51 988]
[17]	Sang H B, He K F 2004 Chin. Phys. Lett. 21 254
[18]	Huang L Y, Luo X S 2006 Chin. Phys. Lett. 23 297
[19]	He G G, Cao Z T 2001 Acta Phys. Sin. 50 2103 (in Chinese) [何国光, 曹志彤 2001 50 2103]
[20]	He G, Chen L, Aihara K 2008 Neurocomputing 71 2794
[21]	He G, Shrimali M D, Aihara K 2007 Physics Letters A 371 228
[22]	He G, Shrimali M D, Aihara K 2008 Neural networks 21 114
[23]	He G G, Zhu P, Chen H P 2010 Acta Phys. Sin. 59 140 (in Chinese) [何国光, 朱萍, 陈宏平 2010 59 140]
[24]	He G, Cao Z, Chen H, Zhu P 2003 International Journal of Modern Physics B 17 4209
[25]	Zhang X, Shen K 2001 Phys. Rev. E 63 046212
[26]	Watanabe M, Aihara K, Kondo S 1996 Electron. Commun. Japan Part III 79 87
[27]	Osana Y, Hagiwara M 1999 Internat. J. Neural Syst. 9 285
[28]	Wang Z, Fan H, Aihara K 2007 Internat. J. Bifur. Chaos 17 3085
[29]	Li Y, Zhu P, Xie X, He G, Aihara K 2012 Phys. Lett. A 376 412
[30]	Sih G C, Tang K K 2012 Theoretical and Applied Fracture Mechanics 61 21
[31]	Freeman W J, Viana Di Prisco G 1986 Brain Theory (Berlin: Springer-Verlag) p97
[32]	Freeman W J 1987 Biological Cybernetics 56 139

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