Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
838459 | Nonlinear Analysis: Real World Applications | 2007 | 13 Pages |
Abstract
Without assuming the boundedness, monotonicity, and differentiability of activation functions and any symmetry of interconnections, we establish some sufficient conditions for the global exponential stability of a unique equilibrium and the existence of periodic solution for the Cohen–Grossberg neural network with time-varying delays. Brouwer's fixed point theorem, matrix theory, a continuation theorem of the coincidence degree and inequality analysis are employed. Our results are all independent of the delays and maybe more convenient to design a circuit network.
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Authors
Chuangxia Huang, Lihong Huang,