Stochastic Approximation in Real Time: A Pipe Line Approach

Abstract

A new approach for stochastic approximation in real time is developed. A number of processors are simultaneously active to carry out a computing task. All processors work on the same system with different starting time. After each iteration, computed date are passed to the next processor on line. Interacting tasks and iterative instructions are carried through pipelining of computation and communication. Asymptotic properties of the algorithm are developed, and comparisons of the performance between the new algorithm and the classical one are made.