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To describe the encoding of continuous stimuli in neural networks, continuous attractors have been recognized as promising models. A continuous attractor is a set of connected stable equilibrium points. It exhibits interesting dynamical properties in many recurrent neural networks. This paper studies the continuous attractors of discrete-time cellular neural networks (DCNNs). The main contribution...
This paper proposes to study the activity invariant sets and exponentially stable attractors of Lotka-Volterra recurrent neural networks. The concept of activity invariant sets deeply describes the property of an invariant set by that the activity of some neurons keeps invariant all the time. Conditions are obtained for locating activity invariant sets. Under some conditions, it shows that an invariant...
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