Accession Number:

ADA024279

Title:

Stochastic Approximation with Correlated Data

Descriptive Note:

Technical rept.

Corporate Author:

COLORADO STATE UNIV FORT COLLINS DEPT OF ELECTRICAL ENGINEERING

Personal Author(s):

Report Date:

1976-04-01

Pagination or Media Count:

31.0

Abstract:

New almost sure convergence results are developed for a special form of the multidimensional Robbins-Monro RM stochastic approximation procedure. The special form treated can be viewed as a stochastic approximation to the solution w w sub o epsilon Rp of the linear equations Rw P, where R is a pxp positive definite symmetric matrix. This special form commonly arises in adaptive signal processing applications. Essentially, previous convergence results for the RM procedure contain a common conditional expectation condition which is extremely difficult if not impossible to satisfy when the training data is a correlated sequence. In contrast, the new convergence results incorporate moment conditions and covariance function decay rate conditions. The ease with which these results can be applied in many cases is illustrated.

Subject Categories:

  • Statistics and Probability
  • Cybernetics
  • Non-Radio Communications

Distribution Statement:

APPROVED FOR PUBLIC RELEASE