Stopping Rules for Linear Stochastic Approximation

Author:

Wada Takayuki,Itani Takamitsu,Fujisaki Yasumasa

Publisher

The Institute of Systems, Control and Information Engineers

Reference16 articles.

1. [1] H. Robbins and S. Monro: A stochastic approximation method; The Annals of Statistics, Vol. 22, No. 3, pp. 400-407 (1951)

2. [2] G. N. Saridis: Stochastic approximation methods for identification and control – A survey; IEEE Transactions on Automatic Control, Vol. 19, No. 6, pp. 798-809 (1974)

3. [4] S. Fujita and T. Fukao: Convergence conditions of dynamic stochastic approximation method for nonlinear stochastic discrete-time dynamic systems; IEEE Transactions on Automatic Control, Vol. 11, No. 10, pp. 715-717 (1972)

4. [6] A. Benveniste, M. Métivier and P. Priouret: Adaptive Algorithms and Stochastic Approximations, Springer-Verlag (1990)

5. [7] B. Bharath and V. S. Borkar: Stochastic approximation algorithms: Overview and recent trends; Sadhana, Vol. 24, No. 4 & 5, pp. 425-452 (1999)

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