Convergence theorems for the Kohonen feature mapping algorithms with VLRPs

DOI10.1016/S0898-1221(96)00236-2zbMath0870.60070OpenAlexW2040936735MaRDI QIDQ679276

Juan-Miguel Gracia

Publication date: 1 September 1997

Published in: Computers \& Mathematics with Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0898-1221(96)00236-2

zbMATH Keywords

stochastic differential equationglobal minimasupermartingaleKohonen feature mapping algorithmvanishing learning rate parameters

Mathematics Subject Classification ID

Martingales with discrete parameter (60G42) Applications of Markov chains and discrete-time Markov processes on general state spaces (social mobility, learning theory, industrial processes, etc.) (60J20)

Related Items (2)

An analysis on neural dynamics with saturated sigmoidal functions ⋮ Kohonen neural networks and genetic classification

Cites Work

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• Self-organization and a.s. convergence of the one-dimensional Kohonen algorithm with non-uniformly distributed stimuli
• Étude d'un processus d'auto-organisation. (Study of a self-organization process)
• Self-organizing maps: Stationary states, metastability and convergence rate
• Self-organizing maps: Ordering, convergence properties and energy functions
• Self-organization and associative memory.
• Stochastic approximation methods for constrained and unconstrained systems
• Modeling Brain Function
• Convergence in Distribution of the One-Dimensional Kohonen Algorithms when the Stimuli are not Uniform

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