DID YOU KNOW? DTIC has over 3.5 million final reports on DoD funded research, development, test, and evaluation activities available to our registered users. Click HERE
to register or log in.
General Convergence Results for Stochastic Approximations Via Weak Convergence Theory,
BROWN UNIV PROVIDENCE R I DIV OF APPLIED MATHEMATICS
Pagination or Media Count:
Using results in the theory of weak convergence of measures and in stability theory for ordinary differential equations, we prove some general convergence theorems for the sequences of random variables which are generated by algorithms of the stochastic approximation type. Such algorithms are used when one wishes to locate, via a recursive Monte-Carlo method, a minimum of a function, under handicap of noisy data. Algorithms for both constrained and unconstrained optimization problems will be considered, and for rather general noise processes. Author
APPROVED FOR PUBLIC RELEASE