WSC '94 Proceedings of the 26th conference on Winter simulation
Randomized Algorithms for Stochastic Approximation under Arbitrary Disturbances
Automation and Remote Control
Gradient Methods for Nonstationary Unconstrained Optimization Problems
Automation and Remote Control
Automation and Remote Control
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Consideration was given to the randomized stochastic approximation algorithm with simultaneous trial input perturbation and two measurements used to optimize the unconstrained nonstationary functional. The upper boundary of the mean-square residual was established under conditions of single differentiability of the functional and almost arbitrary noise. Efficiency of the algorithm was illustrated by an example of stabilization of the resulting estimates for the multidimensional case under dependent observation noise.