Математична модель нейронної схеми типу «K-WINNERS-TAKE-ALL» обробки дискретизованих сигналів

2010;
: pp. 45 – 50
Authors: 

Тимощук П. В.

Національний університет «Львівська політехніка», кафедра систем автоматизованого проектування

Mathematical model of discrete-time K-winners-take-all (KWTA) neural circuit that can identify K maximal from N unknown signals, where <≤ NK1 is proposed. In contrast to existing analogs the model has high resolution, calculation simplicity, it can process signals located in arbitrary finite range and possesses signal ordering preserving property.

1. Bihn L. N. and Chong , H. C. A neural-network contention controller for packet switching networks, IEEE Trans. on Neural Networks 6 (1995) 1402-1410. 2. Calvert B. D. and Marinov C.A. Another K -winnerstake-all analog neural network, IEEE Trans. on Neural Networks 4 (2000) 829-838. 3. Cichocki A. and Unbehauen R. Neural Networks for Optimization and Signal Processing (New York: John Wiley and Sons, 1993). 4. Hopfield J. J. Neurons with graded response have collective computational properties like those of two-state neurons, in: Proc. of Natl. Acad. of Sci. 81 (USA, 1984) 3088-3092. 5. Hu X. and Wang J. An improved dual neural network for solving a class of quadratic programming problems and its k-winners-takeall application, IEEE Trans. on Neural Networks, 19 (2008) 2022-2031. 6. Kwon T. M. and Zervakis M. A parallel sorting network without comparators: A neural-network approach, in: Proc. Int. Joint Conf. on Neural Networks, Vol. 1 (1992) 701-706. 7. Lippmann R. P., Gold B. and Malpass M.L. A comparison of Hamming and Hopfield neural nets for pattern classification, MIT Lincoln Laboratory Technical report TR-769 (1987) 1-37. 8. Liu S. and Wang J. A simplified dual neural network for quadratic programming with its KWTA application, IEEE Trans. on Neural Networks, 17 (2006) 1500-1510. 9. Majani E., Erlanson R. and AbuMostafa Y. On the K -winners-take-all network, in: Advances in Neural Information Process. Syst.. D. S. Touretzky, Vol. 1 (Kaufmann, San Mateo, 1989) 634-642. 10. Marinov C. A. and Calvert B. D. Performance analysis for a K -winners-take-all analog neural network: basic theory, IEEE Trans. on Neural Networks 14 (2003) 766-780. 11. Perfetti R. On the robust design of k-winners-take-all networks, IEEE Trans. on Cir. and Syst.-II: Analog and Digit. Sign. Process., CAS-42 (1995) 55-58. 12. Tymoshchuk P. and Kaszkurewicz E. A Winner-take-all circuit based on second order Hopfield neural networks as building blocks, in: Proc. Int. Joint Conf. on Neural Networks, Vol. II (2003) 891-896. 13. Tymoshchuk P. and Kaszkurewicz E. A winnertake-all circuit using neural networks as building blocks, Neurocomputing 64 (2005) 375-396. 14. Urahama K. and Nagao T. K-Winner-take-all circuit with 0(n) complexity, IEEE Trans. on Neural Networks 6 (1995) 776- 778. 15. Wolfe W. J., Mathis D., Anderson C., Rothman J., Gotler M., Bragy G., Walker R., Duane G. and Alaghband G. K-Winner networks, IEEE Trans. on Neural Networks 2 (1991) 310-315. 16. Yang J. F. and Chen C. M. A Dynamic K-Winners-Take-All Neural Network, IEEE Trans. on Syst., Man and Cyb. 27 (1997) 523~526. 17. Yen J. C. and Chang S., A new first- k -winners neural network, in: Proc. of the ISANN (1997) D-01-D-06. 8. Yen J. C., Guo J. I. and Chen H.-C. A new k -Winners-take all neural network and its array architecture, IEEE Trans. on Neural Networks 9 (1998) 901-912.