On the training and performance of high-order neural networks

DOI10.1016/0025-5564(94)00057-7zbMath0830.92005OpenAlexW2072029523WikidataQ52329063 ScholiaQ52329063MaRDI QIDQ1899213

Nicolaos B. Karayiannis, Anastasios N. Venetsanopoulos

Publication date: 9 October 1995

Published in: Mathematical Biosciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0025-5564(94)00057-7

zbMATH Keywords

capacityapproximationcomposite key-patternsnonlinear associative recalloptimal least squares trainingouter-product ruletraining of high-order neural networks

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Neural networks for/in biological studies, artificial life and related topics (92B20)

Related Items

Pseudo almost periodic solutions for HCNNs with time-varying leakage delays ⋮ Anti-periodic solution for impulsive high-order Hopfield neural networks with time-varying delays in the leakage terms ⋮ Global stability of stochastic high-order neural networks with discrete and distributed delays ⋮ MIXED DELAY-DEPENDENT STABILITY OF HIGH-ORDER NEURAL NETWORKS BASED ON A WEAK COUPLING LMI SET ⋮ On the dynamics in high-order cellular neural networks with time-varying delays ⋮ Mixed time-delays dependent exponential stability for uncertain stochastic high-order neural networks ⋮ An LMI approach to stability analysis of stochastic high-order Markovian jumping neural networks with mixed time delays

Cites Work

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