On the Almost Sure Rate of Convergence of Linear Stochastic Approximation Algorithms

IEEE Transactions on Information Theory

Volumn 50, Issue 2, 2004, Pages 401-409

  Tadić, Vladislav B ^a  

^a UNIVERSITY OF SHEFFIELD   (United Kingdom)

Author keywords

Almost sure rate of convergence; Law of iterated logarithm; Least mean square (LMS) algorithms; Linear stochastic approximation algorithms; Strongly mixing stationary random processes; Uniformly ergodic Markov chains

Indexed keywords

ALGORITHMS; CONVERGENCE OF NUMERICAL METHODS; DIFFERENCE EQUATIONS; EIGENVALUES AND EIGENFUNCTIONS; ITERATIVE METHODS; LEAST SQUARES APPROXIMATIONS; LYAPUNOV METHODS; MARKOV PROCESSES; PROBABILITY; THEOREM PROVING;

ALMOST SURE RATE OF COVERGENCE; LAW OF ITERATED LOGARITHMS; LEAST MEAN SQUARE (LMS) ALGORITHMS; LINEAR STOCHASTIC APPROXIMATION; STRONGLY MIXING STATIONARY RANDOM PROCESSES; UNIFORMLY ERGODIC MARKOV CHAINS;

INFORMATION THEORY;

EID: 1442313216     PISSN: 00189448     EISSN: None     Source Type: Journal    
DOI: 10.1109/TIT.2003.821971     Document Type: Article

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