Stochastic Manhattan learning: Time-evolution operator for the ensemble dynamics

Physical Review E - Statistical Physics, Plasmas, Fluids, and Related Interdisciplinary Topics

Volumn 56, Issue 1, 1997, Pages 1262-1265

  Leen, Todd K ^a   Moody, John E ^a  

^a OREGON HEALTH AND SCIENCE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ITERATIVE METHODS; LEARNING ALGORITHMS; MATHEMATICAL MODELS; PROBABILITY DENSITY FUNCTION; RANDOM PROCESSES;

MANHATTAN LEARNING; TIME EVOLUTION OPERATOR;

LEARNING SYSTEMS;

EID: 0031188949     PISSN: 1063651X     EISSN: None     Source Type: Journal    
DOI: 10.1103/PhysRevE.56.1262     Document Type: Article

References (9)

1. C W. Gardiner, Handbook of Stochastic Methods, 2nd ed. (Springer-Verlag, Berlin, 1990).
2. Todd K. Leen and John E. Moody, Advances in Neural Information Processing Systems, Vol. 5, edited by S. J. Hanson, J. D. Cowan, and C. L. Giles (Kaufmann, San Mateo, CA, 1993), p. 451.
3. G. Radons, H G. Schuster, and D. Werner, in Processing in Neural Systems and Computers, edited by R. Eckmiller, G. Hartmann, and G. Hausek (Elsevier, Amsterdam, 1990).
4. Genevieve B. Orr and Todd K. Leen, Advances in Neural Information Processing Systems, Vol. 5 (Ref. 2), p. 507.
5. Tom M. Heskes, Eddy T. P. Slijpen, and Bert Kappen, Phys. Rev. A46, 5221 (1992).PLRAAN
6. Martin Riedmiller and H. Braun, in Proceedings of the IEEE International Conference on Neural Networks, edited by H. Ruspini (IEEE, San Francisco, 1993).
7. Carsten Peterson and Eric Hartman, Neural Networks2, 475 (1989).NEUCEB
8. L. Ljung, IEEE Trans. Autom. Control.22, 551 (1977).IETAA9
9. Christian Darken and John Moody, in Advances in Neural Information Processing Systems, Vol. 4, edited by J. E. Moody, S. J. Hanson, and R. P. Lipmann (Kaufmann, San Mateo, CA, 1992).