On the convergence of an associative learning algorithm in the presence of noise

DOI10.1080/00207728008967042zbMath0448.62069OpenAlexW2011618436MaRDI QIDQ3894826

Erkki Oja

Publication date: 1980

Published in: International Journal of Systems Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00207728008967042

zbMATH Keywords

residual errorassociative memoriesadaptive neural networkspresence of noiseconvergence of associative learning algorithm

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Pattern recognition, speech recognition (68T10) Stochastic approximation (62L20)

Cites Work

• A theory for the acquisition and loss of neuron specificity in visual cortex
• Adaption and learning in automatic systems. Translated by Z. J. Nikolic
• Regression and the Moore-Penrose pseudoinverse
• Convergence in Iteratively Formed Correlation Matrix Memories
• Analysis of recursive stochastic algorithms
• Convergence of recursive adaptive and identification procedures via weak convergence theory
• On the Construction of Projectors Using Products of Elementary Matrices
• Some Stochastic Approximation Procedures for Use in Process Control

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