A small-size neural network for computing with strange attractors

Neural Networks

Volumn 12, Issue 4-5, 1999, Pages 601-607

  Klotz, A ^a   Brauer K ^a  

^a UNIVERSITY OF TÜBINGEN   (Germany)

Author keywords

Bifurcation diagram; Chaos; Freeman model; Neural networks; Strange attractors

Indexed keywords

BIFURCATION (MATHEMATICS); CALCULATIONS; CHAOS THEORY; CONSTRAINT THEORY; OPTIMIZATION;

BIFURCATION DIAGRAM; FREEMAN MODEL; STRANGE ATTRACTORS;

NEURAL NETWORKS;

ARTICLE; ARTIFICIAL NEURAL NETWORK; CHAOTIC DYNAMICS; MATHEMATICAL COMPUTING; MATHEMATICAL MODEL; MATHEMATICAL PARAMETERS; PRIORITY JOURNAL;

EID: 0345189543     PISSN: 08936080     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0893-6080(99)00029-5     Document Type: Article

References (16)

1. Aihara K., Takabe T., Toyoda M. Chaotic neural networks. Physics Letters A. 144:1990;333-339.
2. Andreyev Y.V., Belsky Y.L., Dmitriev A.S., Kuminov D.A. Information processing using dynamical chaos: neural networks implementation. IEEE Transactions on Neural Networks. 7:(2):1996;290-298.
3. Babloyantz A., Lourenco C. Computation with chaos, a paradigm for cortical activity. Proceedings of the National Academy of Sciences USA. 91:1994;9027.
4. Baird B., Hirsch M.W., Eeckman F. A neural network associative memory for handwritten character recognition using multiple chua attractors. IEEE Transactions on Circuits and Systems II: Analog & Digital Signal Processing. 40:1993;667-674.
5. Chang H.-J., Freeman W.J. Parameter optimization in models of the olfactory neural system. Neural Networks. 9:1996;1-14.
6. Freeman W.J. Simulation of chaotic EEG patterns with a dynamic model of the olfactory system. Biological Cybernetics. 56:1987;139-150.
7. Hirsch M.W., Baird B. Computing with dynamic attractors in neural networks. Biosystems. 34:1995;173-195. Special issue: Biological and evolutionary information processing.
8. Hoff A. Chaos control and neural classification. Zeitschrift für Naturforschung. 49a:1994;589-593.
9. Kushibe M., Liu Y., Ohtsubo J. Associative memory with spatiotemporal chaos control. Physical Reviews E. 53:(5):1996;4502-4508.
10. Sinha S. Controlled transition from chaos to periodic oscillations in a neural network model. Physica A. 224:1996;433-446.
11. Solé R.V., De la Prida L.M. Controlling chaos in discrete neural networks. Physics Letters A. 199:1995;65-69.
12. Tsuda I. Dynamic link of memory-chaotic memory map in non-equilibrium neural networks. Neural Networks. 5:1992;313-326.
13. Van der Maas H.L.J., Verschure P.F.M.J., Molenaar P.C.M. A note on chaotic behaviour in simple neural networks. Neural Networks. 3:1990;119-122.
14. Verschure P.F.M.J. Chaos-based learning. Complex Systems. 5:1991;359-370.
15. Wang X. Period doubling chaos in a simple neural network: an analytical proof. Complex Systems. 5:1991;425-441.
16. Yao Y., Freeman W.J. Model of biological pattern recognition with spatially chaotic dynamics. Neural Networks. 3:1990;153-170.