Iterative processes: A survey of convergence theory using Lyapunov second method

DOI10.1007/BF02366563zbMath0838.90090MaRDI QIDQ1905177

A. N. Nakonechnyi

Publication date: 8 January 1996

Published in: Cybernetics and Systems Analysis (Search for Journal in Brave)

Mathematics Subject Classification ID

Stochastic programming (90C15)

Related Items (5)

Stochastic gradient processes: A survey of convergence theory using Lyapunov second method ⋮ Optimization of risk processes ⋮ Monte-Carlo estimate of the probability of ruin in a compound Poisson model of risk theory ⋮ Optimization methods for compound Poisson risk processes ⋮ Nonstationary law of large numbers for dependent random variables and its application in stochastic optimization

Cites Work

• Recursive estimation of the mode of a multivariate distribution
• Convergence of general iteration schemes
• Procedure of stochastic approximation with disturbances at the input
• Adaptive optimization of the Monte-Carlo method
• Probability-theoretical analog of the vector Lyapunov function method
• Minimization of functions having Lipschitz continuous first partial derivatives
• Stability and positive supermartingales
• Passive stochastic approximation
• The Lyapunov matrix-function
• Necessary and sufficient conditions for convergence of iteration algorithms of nonlinear programming
• Stochastic approximation methods for identification and control--A survey
• Convergence and stability of distributed stochastic iterative processes
• On the theory of stability of motion
• Vector Lyapunov Functions
• A Gradient Technique of Adaptive Monte Carlo
• Multidimensional Stochastic Approximation Methods
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