Competitive Layer Model of Discrete-Time Recurrent Neural Networks with LT Neurons

DOI10.1162/NECO_A_00004-ZHOUzbMath1195.68085DBLPjournals/neco/ZhouZ10OpenAlexW1994173832WikidataQ51700555 ScholiaQ51700555MaRDI QIDQ3583499

Wei Zhou, Jacek M. Zurada

Publication date: 17 August 2010

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

Full work available at URL: https://doi.org/10.1162/neco_a_00004-zhou

zbMATH Keywords

discrete-time recurrent neural networks with linear threshold neurons

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Computing methodologies for image processing (68U10) Pattern recognition, speech recognition (68T10)

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Cites Work

• A Competitive-Layer Model for Feature Binding and Sensory Segmentation
• Lyapunov Functions for Neural Nets with Nondifferentiable Input-Output Characteristics
• Matrix Analysis
• Selectively Grouping Neurons in Recurrent Networks of Lateral Inhibition
• Sufficient and necessary conditions for global exponential stability of discrete-time recurrent neural networks
• Permitted and Forbidden Sets in Symmetric Threshold-Linear Networks
• Multistability Analysis for Recurrent Neural Networks with Unsaturating Piecewise Linear Transfer Functions
• Activity Invariant Sets and Exponentially Stable Attractors of Linear Threshold Discrete-Time Recurrent Neural Networks
• Global stability of a class of discrete-time recurrent neural networks
• Analysis of Cyclic Dynamics for Networks of Linear Threshold Neurons

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