Dynamical properties of learning process of weakly nonlinear and nonlinear neurons

DOI10.1016/S0362-546X(00)00105-XzbMath1017.92002WikidataQ123956614 ScholiaQ123956614MaRDI QIDQ5930642

Andrzej Bielecki

Publication date: 4 September 2003

Published in: Nonlinear Analysis. Real World Applications (Search for Journal in Brave)

zbMATH Keywords

discretizationtopological conjugacyartivicial neural networksEuler methodlearning processnonlinear neurons

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)

Related Items (5)

Dynamical properties of the reaction-diffusion type model of fast synaptic transport ⋮ Dynamical properties of a perceptron learning process: structural stability under numerics and shadowing ⋮ Properties and applications of weakly nonlinear neurons. ⋮ Shadowing property in analysis of neural networks dynamics. ⋮ Topological conjugacy of discrete time-map and Euler discrete dynamical systems generated by a gradient flow on a two-dimensional compact manifold

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