Continuous stochastic approximation with semi-Markov switchings in the diffusion approximation scheme

2007 ◽  
Vol 43 (4) ◽  
pp. 605-612 ◽  
Author(s):  
Ya. M. Chabanyuk
Keyword(s):  
Stochastic Approximation ◽  
Diffusion Approximation ◽  
Approximation Scheme

A two Timescale Stochastic Approximation Scheme for Simulation-Based Parametric Optimization

1998 ◽  
Vol 12 (4) ◽  
pp. 519-531 ◽  
Author(s):  
Shalabh Bhatnagar ◽  
Vivek S. Borkar
Keyword(s):  
Stochastic Approximation ◽  
Perturbation Analysis ◽  
Parametric Optimization ◽  
Approximation Scheme ◽  
Infinitesimal Perturbation Analysis ◽  
Simulation Based ◽  
Infinitesimal Perturbation ◽  
Two Timescale Stochastic Approximation

A two timescale stochastic approximation scheme which uses coupled iterations is used for simulation-based parametric optimization as an alternative to traditional “infinitesimal perturbation analysis” schemes. It avoids the aggregation of data present in many other schemes. Its convergence is analyzed, and a queueing example is presented.

scholarly journals On fixed gain recursive estimators with discontinuity in the parameters

2019 ◽  
Vol 23 ◽  
pp. 217-244
Author(s):  
Huy N. Chau ◽  
Chaman Kumar ◽  
Miklós Rásonyi ◽  
Sotirios Sabanis
Keyword(s):  
Stochastic Approximation ◽  
Approximation Scheme ◽  
Tracking Error ◽  
Mixing Condition ◽  
Underlying Process ◽  
Recursive Estimators

In this paper, we estimate the expected tracking error of a fixed gain stochastic approximation scheme. The underlying process is not assumed Markovian, a mixing condition is required instead. Furthermore, the updating function may be discontinuous in the parameter.

Distributed Parameter Identification Using the Method of Characteristics

1971 ◽  
Vol 93 (2) ◽  
pp. 73-78 ◽  
Author(s):  
William T. Carpenter ◽  
Michael J. Wozny ◽  
Raymond E. Goodson
Keyword(s):  
Distributed Systems ◽  
Parameter Identification ◽  
Stochastic Approximation ◽  
Method Of Characteristics ◽  
Approximation Scheme ◽  
Multidimensional Systems ◽  
Distributed Parameter ◽  
The Method Of Characteristics ◽  
Noisy Measurements ◽  
And Diffusion

A method is presented for estimating parameters in distributed systems which can be analyzed by the method of characteristics. Both the very real problems of noisy measurements and limited available measurement transducers are discussed in some depth. Convergent algorithms are developed using a Robbins-Munro stochastic approximation scheme. The extension of these methods to the identification of function multidimensional systems, and diffusion terms is considered.

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