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Article
A Novel Adaptive Algorithm with Optimum Rates of Convergence
3rd Forum on Numerics and Modeling for Partial Differential Equations, NUMPEDS 2000 proceedings
  • Sally S. L. Shao, Cleveland State University
  • Percy P. C. Yip, AI WARE, Inc
Document Type
Conference Proceeding
Publication Date
1-1-2000
Disciplines
Abstract
We propose a new adaptive algorithm with decreasing step-size for stochastic approximations. The use of adaptive algorithm is widely spread in various applications across the fields such as system identification and adaptive control. We analyze the rate of convergence of the proposed algorithms. An averaging algorithm, on its optimality of the rate of convergence, is using to control the step sizes. Our proofs are based on recent results in stochastic approximations and Guass approximation Theorem.
Citation Information
S. Shao and P. P. C. Yip. (2000) A novel adaptive algorithm with optimum rates of convergence. 3rd Forum on Numerics and Modeling for Partial Differential Equations, NUMPEDS 2000 proceedings, 1-20.