Contractivity of a Markov operator on the space of normalised positive distributions

DOI10.1016/j.neunet.2013.03.005zbMath1296.92189OpenAlexW2089858564WikidataQ47901469 ScholiaQ47901469MaRDI QIDQ459422

Israel Ncube

Publication date: 9 October 2014

Published in: Neural Networks (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.neunet.2013.03.005

zbMATH Keywords

convergencelearning algorithmsstochastic approximationFrobenius-Perron operatorartificial neural networksstationary densities

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Stability theory of functional-differential equations (34K20) Stochastic approximation (62L20) Protein sequences, DNA sequences (92D20)

Cites Work

• Stochastic approximation methods for constrained and unconstrained systems
• Chaos, fractals, and noise: Stochastic aspects of dynamics.
• Stationary densities and the stochastic approximation of a certain class of random algorithms
• Analysis of recursive stochastic algorithms
• Convergence of stochastic algorithms: from the Kushner–Clark theorem to the Lyapounov functional method
• Folding maps and functional equations
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