AbstractRobust estimation of parameters may be obtained via stochastic approximation algorithms. This paper deals with the properties of a recursive estimator of a location parameter in a stationary strongly regular process. Adaptive estimators of particular interest are also studied
AbstractMany generalizations of the Robbins-Monro process have been proposed for the purpose of recu...
International audienceThis paper provides an optimization-based approach to assure the strict positi...
Main adaptive control design approaches assume that a suitable dynamic model of the controlled proce...
AbstractRobust estimation of parameters may be obtained via stochastic approximation algorithms. Thi...
AbstractThis paper treats strong convergence of adaptive multivariate recursive M-estimators of loca...
In this paper we present a recursive algorithm that produces estimators of an unknown parameter that...
AbstractRecursive parameter estimation in diffusion processes is considered. First, stability and as...
We propose a recursive algorithm for tracking a multi-dimensional time-varying parameter of a time s...
International audienceIn this paper, we extend convergence conditions for the parameter adaptation a...
The constant stepsize analog of Gelfand-Mitter type discrete-time stochastic recursive algorithms is...
AbstractIn this paper we present a recursive algorithm that produces estimators of an unknown parame...
The convergence properties of a very general class of adaptive recursive algorithms for the identifi...
The constant stepsize analog of Gelfand-Mitter type discrete-time stochastic recursive algorithms is...
AbstractLet {Xj}j = − ∞∞ be a vector-valued stationary process with a first-order univariate probabi...
A recursive maximum-likelihood algorithm (RML) is proposed that can be used when both the observatio...
AbstractMany generalizations of the Robbins-Monro process have been proposed for the purpose of recu...
International audienceThis paper provides an optimization-based approach to assure the strict positi...
Main adaptive control design approaches assume that a suitable dynamic model of the controlled proce...
AbstractRobust estimation of parameters may be obtained via stochastic approximation algorithms. Thi...
AbstractThis paper treats strong convergence of adaptive multivariate recursive M-estimators of loca...
In this paper we present a recursive algorithm that produces estimators of an unknown parameter that...
AbstractRecursive parameter estimation in diffusion processes is considered. First, stability and as...
We propose a recursive algorithm for tracking a multi-dimensional time-varying parameter of a time s...
International audienceIn this paper, we extend convergence conditions for the parameter adaptation a...
The constant stepsize analog of Gelfand-Mitter type discrete-time stochastic recursive algorithms is...
AbstractIn this paper we present a recursive algorithm that produces estimators of an unknown parame...
The convergence properties of a very general class of adaptive recursive algorithms for the identifi...
The constant stepsize analog of Gelfand-Mitter type discrete-time stochastic recursive algorithms is...
AbstractLet {Xj}j = − ∞∞ be a vector-valued stationary process with a first-order univariate probabi...
A recursive maximum-likelihood algorithm (RML) is proposed that can be used when both the observatio...
AbstractMany generalizations of the Robbins-Monro process have been proposed for the purpose of recu...
International audienceThis paper provides an optimization-based approach to assure the strict positi...
Main adaptive control design approaches assume that a suitable dynamic model of the controlled proce...
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