The constant stepsize analog of Gelfand-Mitter type discrete-time stochastic recursive algorithms is shown to track an associated stochastic differential equation in the strong sense, i.e., with respect to an appropriate divergence measure
AbstractWe study sufficient conditions under which a sequence of stochastic processes (Xn(t))t ≥ 0 c...
AbstractA convergence theorem for the continuous weak approximation of the solution of stochastic di...
We study the almost sure asymptotic behaviour of stochastic approximation algorithms for the search ...
The constant stepsize analog of Gelfand-Mitter type discrete-time stochastic recursive algorithms is...
Stochastic approximation algorithms are iterative procedures which are used to approximate a target ...
We study sufficient conditions under which a sequence of stochastic processes (Xn(t))t >= 0 can be a...
In this article we consider diffusion approximations for a general class of random recursions. Such ...
Stochastic approximation is a common paradigm for many stochastic recursions arising both as algorit...
AbstractThis paper is a survey of strong discrete time approximations of jump-diffusion processes de...
Stochastic approximation is a common paradigm for many stochastic recursions arising both as algorit...
Under general conditions on the observation processes the almost sure convergence properties of an u...
We present a sufficient and necessary condition for the convergence of stochastic approximation algo...
AbstractWe consider a rather general one-dimensional stochastic approximation algorithm where the st...
In this paper, we develop a strong Milstein approximation scheme for solving stochastic delay differ...
We present a sufficient and necessary condition for the convergence of stochastic approximation algo...
AbstractWe study sufficient conditions under which a sequence of stochastic processes (Xn(t))t ≥ 0 c...
AbstractA convergence theorem for the continuous weak approximation of the solution of stochastic di...
We study the almost sure asymptotic behaviour of stochastic approximation algorithms for the search ...
The constant stepsize analog of Gelfand-Mitter type discrete-time stochastic recursive algorithms is...
Stochastic approximation algorithms are iterative procedures which are used to approximate a target ...
We study sufficient conditions under which a sequence of stochastic processes (Xn(t))t >= 0 can be a...
In this article we consider diffusion approximations for a general class of random recursions. Such ...
Stochastic approximation is a common paradigm for many stochastic recursions arising both as algorit...
AbstractThis paper is a survey of strong discrete time approximations of jump-diffusion processes de...
Stochastic approximation is a common paradigm for many stochastic recursions arising both as algorit...
Under general conditions on the observation processes the almost sure convergence properties of an u...
We present a sufficient and necessary condition for the convergence of stochastic approximation algo...
AbstractWe consider a rather general one-dimensional stochastic approximation algorithm where the st...
In this paper, we develop a strong Milstein approximation scheme for solving stochastic delay differ...
We present a sufficient and necessary condition for the convergence of stochastic approximation algo...
AbstractWe study sufficient conditions under which a sequence of stochastic processes (Xn(t))t ≥ 0 c...
AbstractA convergence theorem for the continuous weak approximation of the solution of stochastic di...
We study the almost sure asymptotic behaviour of stochastic approximation algorithms for the search ...
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