Neural network learning based on stochastic sensitivity analysis

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics

Volumn 27, Issue 1, 1997, Pages 132-135

  Koda, Masato ^a  

^a IBM JAPAN LTD   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

BACKPROPAGATION; CORRELATION METHODS; LEARNING SYSTEMS; LYAPUNOV METHODS; MATHEMATICAL MODELS; SENSITIVITY ANALYSIS; WHITE NOISE;

HEBBIAN LEARNING LAWS; STOCHASTIC LEARNING LAWS;

NEURAL NETWORKS;

EID: 0031078838     PISSN: 10834419     EISSN: None     Source Type: Journal    
DOI: 10.1109/3477.552193     Document Type: Article

References (17)

1. M. A. Cohen and S. Grossberg, "Absolute stability of global pattern formation and parallel memory storage by competitive neural networks," IEEE Trans. Syst., Man, Cybern., vol. SMC-13, pp. 815-826, 1983.
2. D. K. Dacol and H. Rabitz, "Sensitivity analysis of stochastic kinetic models," J. Math. Phys., vol. 25, pp. 2716-2727, 1984.
3. S. Grossberg, "Nonlinear neural networks: Principles, mechanisms, and architectures," Neural Networks, vol. 1, pp. 17-61, 1988.
4. M. Koda, "Sensitivity analysis of time-delay systems," Int. J. Syst. Sci., vol. 12, pp. 1389-1397, 1981.
5. _, "Sensitivity analysis of singularly perturbed systems," Int. J. Syst. Sci., vol. 13, pp. 909-919, 1982.
6. _, "Sensitivity analysis of atmospheric diffusion equation," Atmos. Environ., vol. 16, pp. 2595-2601, 1982.
7. _, "Sensitivity analysis of descriptor distributed parameter systems," Int. J. Syst. Sci., vol. 19, pp. 2103-2114, 1988.
8. _, "Sensitivity analysis of stochastic dynamical systems," Int. J. Syst. Sci., vol. 23, pp. 2187-2195, 1992.
9. _, "Stochastic sensitivity analysis method for neural network learning," Int. J. Syst. Sci., vol. 26, pp. 703-711, 1995.
10. M. Koda, A. Dogru, and J. H. Seinfeld, "Sensitivity analysis of partial differential equations with application to reaction and diffusion processes," J. Comp. Phys., vol. 30, pp. 259-282, 1979.
11. M. Koda and J. H. Seinfeld, "Sensitivity analysis of distributed parameter systems," IEEE Trans. Automat. Contr., vol. AC-27, pp. 951-955, 1982.
12. B. Kosko, "Structural stability of unsupervised learning in feedback neural networks," IEEE Trans. Automat. Contr., vol. 36, pp. 785-792, 1991.
13. K. Matsuoka, "Learning and evolution of neural nets," (in Japanese), J. SICE, vol. 32, pp. 843-847, 1993.
14. K. Matsuoka and T. Tokunari, "Learning of neural nets that involve spontaneous random signals," in Proc. SICE'92, pp. 805-806.
15. B. A. Pearlmutter, "Learning state space trajectories in recurrent neural network," Neural Computat., vol. 1, pp. 263-269, 1989.
16. F. J. Pineda, "Generalization of back-propagation to recurrent neural network," Phys. Rev. Lett., vol. 59, pp. 2229-2232, 1987.
17. A.V. Skorohod, Studies in the Theory of Random Processes. Reading, MA: Addison-Wesley, 1965.