Cycle-symmetric matrices and convergent neural networks

DOI10.1016/S0167-2789(00)00134-2zbMath0986.92004WikidataQ128024711 ScholiaQ128024711MaRDI QIDQ5940290

Chih-Wen Weng, Chih-Wen Shih

Publication date: 4 June 2002

Published in: Physica D (Search for Journal in Brave)

zbMATH Keywords

Lyapunov functionconvergence of dynamicscycle-symmetric matrix

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Dynamical systems in biology (37N25) Neural networks for/in biological studies, artificial life and related topics (92B20) Homoclinic and heteroclinic solutions to ordinary differential equations (34C37)

Related Items (7)

New exponential stability results for delayed neural networks with time varying delays ⋮ Global attraction and stability for Cohen--Grossberg neural networks with delays ⋮ Skew-signings of positive weighted digraphs ⋮ Global consensus for discrete-time competitive systems ⋮ Transversal homoclinic orbits in a transiently chaotic neural network ⋮ Robust exponential stability of uncertain fuzzy Cohen-Grossberg neural networks with time-varying delays ⋮ ON THE TEMPLATES CORRESPONDING TO CYCLE-SYMMETRIC CONNECTIVITY IN CELLULAR NEURAL NETWORKS

Cites Work

• The symmetrization of matrices by diagonal matrices
• Competition, decision, and consensus
• Combinatorially symmetric matrices
• A class of convergent neural network dynamics
• Absolute stability of global pattern formation and parallel memory storage by competitive neural networks
• Cellular neural networks: theory
• Neurons with graded response have collective computational properties like those of two-state neurons.
• COMPLETE STABILITY FOR STANDARD CELLULAR NEURAL NETWORKS
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