Cellular Neural Networks: Theory

IEEE Transactions on Circuits and Systems

Volumn 35, Issue 10, 1988, Pages 1257-1272

  Chua, Leon O ^a   Yang, Lin ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AUTOMATA THEORY; COMPUTER SIMULATION; ELECTRIC NETWORKS, NONLINEAR; SIGNAL PROCESSING; SYSTEM STABILITY -- LYAPUNOV METHODS;

CELLULAR AUTOMATA; CELLULAR NEURAL NETWORKS; INFORMATION-PROCESSING SYSTEMS; LARGE-SCALE NONLINEAR ANALOG CIRCUITS; REAL-TIME PARALLEL SIGNAL PROCESSING;

SYSTEMS SCIENCE AND CYBERNETICS;

EID: 0024088955     PISSN: 00984094     EISSN: None     Source Type: Journal    
DOI: 10.1109/31.7600     Document Type: Article

References (27)

1. L. O. Chua and L. Yang, “Cellular neural networks: Applications”, IEEE Trans. Circuits Syst., pp. 1273-1290, this issue.
2. J. J. Hopfield, “Neural networks and physical systems with emergent computational abilities”, Proc. Natl. Acad. Sci. USA., vol. 79, pp. 2554-2558, 1982.
3. J. J. Hopfield and D. W. Tank “'Neural' computation of decisions in optimization problems”, Biol. Cybern., vol. 52, pp. 141-152, 1985.
4. J. J. Hopfield and D. W. Tank, “Computing with neural circuits: amodel”, Science (USA), vol. 233, no. 4764, pp. 625-633, 1986.
5. D. W. Tank and J. J. Hopfield, “Simple 'neuron' optimizationnetworks: An A/D converter, signal decision circuit, and a linearprogramming circuit”, IEEE Trans. Circuits Syst., vol. CAS-33, pp.533-541, 1986.
6. M. P. Kennedy and L. O. Chua, “Unifying the Tank and Hopfieldlinear programming circuit and the canonical nonlinear programming circuit of Chua and Lin”, IEEE Trans. Circuits Syst., vol. CAS-34, pp. 210-214, 1987.
7. T. Kohonen, Self-Organization and Associative Memory. NewYork: Springer-Verlag, 1984.
8. C. Koch J. Marroquin, and A. Yuille, “Analog 'neuronal' networksin early vision”, Proc. Natl. Acad. Sci. USA, vol. 83, p. 4263-4267, 1986.
9. I. Kanter and H. Sompolinsky, “Associative recall of memorywithout errors”, Phys. Rev. A, vol. 35, no. 1, pp. 380-392, 1987.
10. J. Buhmann and K. Schulten, “Associative recognition and storagein a model network of physiological neurons”, Biol. Cybern., vol. 54, pp. 319-335, 1986.
11. M. P. Kennedy and L. O. Chua, “Neural networks for nonlinearprogramming, IEEE Trans. Circuits Syst., vol. 35, pp. 554-562, May 1988.
12. L. O. Chua and T. Lin, “A neural network approach to transformimage coding”, Int. J. Circuit Theory Appi, to be published.
13. L. O. Chua, C. A. Desoer, and E. S. Kuh, Linear and NonlinearCircuits. New York: McGraw-Hill, 1987.
14. Leon O. Chua, Introduction to Nonlinear Network Theory. NewYork: McGraw-Hill, 1969.
15. Special Issue on Chaotic Systems, Proc. IEEE, Aug. 1987.
16. L. O. Chua and R. N. Madan, “The sights and sounds of chaos”, IEEE Circuits Devices Mag., pp. 3-13, Jan., 1988.
17. L. O. Chua and Y. Liao, “PWLSPICE: SPICE for piecewiSElinearcircuits”, in preparation.
18. T. Quarles, A. R. Newton, D. O. Pederson, and A. SangiovannIVincentelli, “SPICE.3A7 User's Guide”, Dep. Elect. Eng. andComp. Sci., Univ. of California, Berkeley, June 13, 1986.
19. L. O. Chua and P. M. Lin, Computer Aided Analysis of ElectronicCircuits: Algorithms and Computational Techniques. EnglewoodCliffs, NJ: Prentice-Hall, 1975.
20. L. O. Chua and R. L. P. Ying, “Finding all solutions of piecewiSElinear circuits”, J. Circuit Theory Appl., vol. 10, pp. 201-229, 1982.
21. L. O. Chua and A. C. Deng, “Canonical piecewiSElinear analysis:Generalized breakpoint hopping algorithm”, Int. J. Circuit TheoryAppl., vol. 14, pp. 35-52, Jan. 1986.
22. S. Wolfram (Eds.), Theory and Applications of Cellular Automata. New York: World Scientific, 1986.
23. N. Packard and S. Wolfram, “Two-dimensional cellular automata”, J. Stat. Phys., vol. 38, nos. 5/6, pp. 901-946, 1985.
24. T. Toffoli and N. Margolus, Cellular Automata Machines - A New Environment for Modeling. Cambridge, MA: M.I.T. Press, 1986.
25. K. Preston, Jr. and M. J. B. Duff, Modern Cellular Automata:Theory and Applications. New York, Plenum, 1984.
26. J. J. Hopfield, “Neurons with graded response have collectivecomputational properties like those of two-state neurons”, in Proc. Natl. Acad. Sci. USA, vol. 81, pp. 3088-3092, 1984.
27. M. P. Kennedy and L. O. Chua, “Circuit theoretic solutions forneural networks-An old approach to a new problem”, in Proc. First IEEE Conf. on Neural Networks, vol. 2, pp. 169-176, SanDiego, CA, June 21 - 24, 1987.