Associative memory with a controlled chaotic neural network

Neurocomputing

Volumn 71, Issue 13-15, 2008, Pages 2794-2805

  He, Guoguang ^a,b,c   Chen, Luoan ^a,c,d   Aihara, Kazuyuki ^a,c  

^a UNIVERSITY OF TOKYO   (Japan)

^b ZHEJIANG UNIVERSITY   (China)

^c INSTITUTE OF INDUSTRIAL SCIENCE   (Japan)

^d OSAKA SANGYO UNIVERSITY   (Japan)

Author keywords

Associative memory; Chaotic neural networks; Controlling chaos; Information processing

Indexed keywords

ADAPTIVE CONTROL SYSTEMS; ASSOCIATIVE STORAGE; CHAOS THEORY; DATA PROCESSING; DYNAMICS; MEMORY ARCHITECTURE; NEURAL NETWORKS; PATTERN RECOGNITION;

ADAPTIVE CONTROL METHODS; ASSOCIATIVE DYNAMICS; ASSOCIATIVE MEMORY; CHAOTIC BEHAVIORS; CHAOTIC NEURAL NETWORK; CONTROLLING CHAOS; DELAY FEEDBACK CONTROL; SCALING PARAMETER;

ASSOCIATIVE PROCESSING;

ARTICLE; ASSOCIATIVE MEMORY; DYNAMICS; FEASIBILITY STUDY; FEEDBACK SYSTEM; INFORMATION PROCESSING; MATHEMATICAL ANALYSIS; MATHEMATICAL COMPUTING; MATHEMATICAL PARAMETERS; MEMORY CONSOLIDATION; NERVE CELL NETWORK; PATTERN RECOGNITION; PRIORITY JOURNAL; RECALL; SIGNAL TRANSDUCTION;

EID: 56449107866     PISSN: 09252312     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neucom.2007.09.005     Document Type: Article

References (29)

1. M. Adachi, K. Aihara, Associative dynamics in a chaotic neural network, Neural Networks 10 (1997) 83-98.
2. K. Aihara, G. Matsumoto, Chaotic oscillations and bifurcations in squid giant axons, in: A.V. Holden (Ed.), Chaos, Princeton University Press, Princeton, 1986, pp. 257-269.
3. K. Aihara, T. Takabe, M. Toyoda, Chaotic neural networks, Phys. Lett. A 144 (1990) 333-340.
4. L. Chen, K. Aihara, Chaotic simulated annealing by a neural network model with transient chaos, Neural Networks 8 (6) (1995) 915-930.
5. L. Chen, K. Aihara, Global searching ability of chaotic neural networks, IEEE Trans. Circuits Syst. I 46 (8) (1999) 974-993.
6. N. Crook, T. Scheper, V. Pathirana, Self-organised dynamic recognition states for chaotic neural networks, Inf. Sci. 150 (2003) 59-75.
7. H. Degn, A.V. Holden, L.F. Olsen (Eds.), Chaos in Biological Systems, Plenum, New York, 1987.
8. W.J. Freeman, Simulation of chaotic EEG patterns with a dynamic model of the olfactory system, Biol. Cybern. 56 (1987) 139-150.
9. V. Gimenez-Martinez, A modified Hopfield auto-associative memory with improved capacity, IEEE Trans. Neural Networks 11 (2000) 867-878.
10. G. He, Z. Cao, H. Chen, P. Zhu, Controlling chaos in a chaotic neural network based on phase space constraint, Int. J. Mod. Phys. B 17 (2003) 4209-4214.
11. G. He, Z. Cao, P. Zhu, H. Ogura, Controlling chaos in a chaotic neural network, Neural Networks 16 (2003) 1195-1200.
12. G. He, J. Kuroiwa, H. Ogura, P. Zhu, Z. Cao, P. Chen, A type of delay feedback control of chaotic dynamics in a chaotic neural network, IEICE Trans. Fundam. E 87-A (2004) 1765-1771.
13. A.L. Hodgkin, A.F. Huxley, A quantitative description of membrane current and its application to conduction and excitation in nerve, J. Physiol. (London) 117 (1952) 500-544.
14. J.J. Hopfield, Neural networks and physical systems with emergent collective computation abilities, in: Proceedings of National Academy of Sciences, USA, vol. 79, 1982, pp. 2554-2558.
15. G. Hu, Z. Qu, Controlling spatiotemporal chaos in coupled map lattice systems, Phys. Rev. Lett. 72 (1994) 68-77.
16. E.R. Hunt, Stabling high-period orbits in a chaotic system: The diode resonator, Phys. Rev. Lett. 67 (1991) 1953-1955.
17. T. Kohonen, Self-organized formation of topologically correct feature maps, Biol. Cybern. 43 (1982) 59-69.
18. J. Kuroiwa, S. Nara, K. Aihara, Response properties of a single chaotic neuron to stochastic inputs, Int. J. Bifurcation Chaos 5 (2001) 1447-1460.
19. M. Kushibe, Y. Liu, J. Ohtsubo, Associative memory with spatiotemporal chaos control, Phys. Rev. E 53 (5) (1996) 4502-4508.
20. G. Matsumoto, K. Aihara, Y. Hanyu, N. Takahashi, S. Yoshizawa, J. Nagumo, Chaos and phase locking in normal squid axons, Phys. Lett. A 123 (1987) 162-166.
21. R. McEliece, E. Posner, E. Rodemich, S. Venkatesh, The capacity of the Hopfield associative memory, IEEE Trans. Inf. Theory 33 (1987) 461-482.
22. S. Mizutani, T. Sano, T. Uchiyama, N. Sonehara, Controlling chaos in chaotic neural networks, Electron. Commun. Jpn. Part 3 81 (1998) 73-82.
23. J. Nagumo, S. Sato, On a response characteristic of a mathematical neuron model, Kybernetik 10 (1972) 155-164.
24. K. Nakamura, M. Nakagawa, On the associative model with parameter controlled chaos neurons, J. Phys. Soc. Jpn 62 (8) (1993) 2941-2955.
25. S. Nara, P. Davis, Learning feature constraints in a chaotic neural memory, Phys. Rev. E 55 (1997) 826-830.
26. E. Ott, C. Grebogi, J.A. Yorke, Controlling chaos, Phys. Rev. Lett. 64 (1990) 1196-1199.
27. K. Pyragas, Continuous control of chaos by self-controlling feedback, Phys. Lett. A 170 (1992) 421-428.
28. D.E. Rumelhart, G.E. Hintont, R.J. Williams, Learning representations by back-propagating errors, Nature 323 (1986) 533-536.
29. L.P. Wang, Effects of noise in training patterns on the memory capacity of the fully connected binary Hopfield neural network: A mean-field theory and simulations, IEEE Trans. Neural Networks 9 (4) (1998) 697-704.