A randomized stochastic approximation algorithm for self-learning

Automation and Remote Control

Volumn 66, Issue 8, 2005, Pages 1239-1248

  Granichin, O N ^a   Izmakova, O A ^a  

^a ST PETERSBURG STATE UNIVERSITY   (Russian Federation)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; APPROXIMATION THEORY; COMPUTER AIDED DESIGN; ESTIMATION; MATHEMATICAL MODELS; RANDOM PROCESSES;

COMPUTER-AIDED MODELING; SELF-LEARNING; STOCHASTIC APPROXIMATION;

LEARNING SYSTEMS;

EID: 24144470105     PISSN: 00051179     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10513-005-0165-3     Document Type: Article

References (12)

1. Aizerman, M.A., Braverman, E.M., and Rozonoer, L.I., Metod potentsial'nykh funktsii v teorii obucheniya mashin (The Potential Functions Method in Machine Learning Theory), Moscow: Nauka, 1970.
2. Fomin, V.N., Matematicheskaya teoriya obuchaemykh sistem (Mathematical Theory of Learning Systems), Leningrad: Leningrad. Gos. Univ., 1976.
3. Fomin, V.N., Rekurrentnoe otsenivanie i adaptivnaya fil'tratsiya (Recurrent Estimation and Adaptive Filtration), Moscow: Nauka, 1984.
4. Granichin, O.N. and Polyak, B.T., Randomizirovannye algoritmy otsenivaniya i optimizatsii pri pochti proizvol'nykh pomekhakh (Randomized Estimation Algorithms and Optimization under Almost Arbitrary Perturbations), Moscow: Nauka, 2003.
5. Haykin, S., Neural Networks: A Comprehensive Foundation, New York: Macmillan, 1984.
6. White, H., Artifical Neural Networks, Oxford: Blackwell, 1992.
7. Vidyasagar, M., A Theory of Learning and Generalization with Applications to Neural Networks and Control Systems, London: Springer, 1997.
8. Poznyak, A.S., Sanches, E.N., and Wen, Yu., Dynamic Neural Networks for Nonlinear Control: Identification, State Estimation and Trajectory Tracking, Singapore: World Scientific, 2001.
9. Granichin, O.N., Stochastic Approximation with Input Perturbation under Dependent Observation Noises, Vestn. Leningrad. Gos. Univ., 1989, ser. 1, no. 4, pp. 27-31.
10. Polyak, B.T., Vvedenie v optimizatsiyu, Moscow: Nauka, 1983.
11. Translated under the title Introduction to Optimization, New York: Optimization Software, 1987.
12. Robbins, H. and Siegmuud, D., A Convergence Theorem for Nonnegative Almost Super-Marlingales and Some Applications, in Optimization Methods of Statistics, Rustagi, J.S., Ed., New York: Academic, 1971, pp. 233-257.