THE ŁOJASIEWICZ EXPONENT AT AN EQUILIBRIUM POINT OF A STANDARD CNN IS 1/2

DOI10.1142/S0218127406016008zbMath1192.37116MaRDI QIDQ3579258

Mauro Forti, Alberto Tesi

Publication date: 6 August 2010

Published in: International Journal of Bifurcation and Chaos (Search for Journal in Brave)

zbMATH Keywords

cellular neural networksexponential convergencecomplete stabilityfinite trajectory lengthłojasiewicz inequality

Mathematics Subject Classification ID

Neural biology (92C20) Dynamical systems in biology (37N25) Stability of solutions to ordinary differential equations (34D20) Neural nets applied to problems in time-dependent statistical mechanics (82C32) Fixed points and periodic points of dynamical systems; fixed-point index theory; local dynamics (37C25)

Related Items (8)

Łojasiewicz inequality and exponential convergence of the full‐range model of CNNs ⋮ Comparison of convergence and stability properties for the state and output solutions of neural networks ⋮ Hölder-type global error bounds for non-degenerate polynomial systems ⋮ On continuous selections of polynomial functions ⋮ ON THE MARGIN OF COMPLETE STABILITY FOR A CLASS OF CELLULAR NEURAL NETWORKS ⋮ On the Łojasiewicz exponent of Kuramoto model ⋮ A neurodynamic approach to convex optimization problems with general constraint ⋮ LIMIT SET DICHOTOMY AND CONVERGENCE OF SEMIFLOWS DEFINED BY COOPERATIVE STANDARD CNNs

Cites Work

• Simultaneous equations models in applied search theory
• Separation of algebraic sets and the Łojasiewicz exponent of polynomial mappings
• Cellular neural networks: theory
• Generalized Neural Network for Nonsmooth Nonlinear Programming Problems
• Absolute Stability of Analytic Neural Networks: An Approach Based on Finite Trajectory Length
• A NEW METHOD TO ANALYZE COMPLETE STABILITY OF PWL CELLULAR NEURAL NETWORKS

This page was built for publication: THE ŁOJASIEWICZ EXPONENT AT AN EQUILIBRIUM POINT OF A STANDARD CNN IS 1/2