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- W2149018240 abstract "We present a new method of analyzing the dynamics of self-organizing neural networks with different time scales based on the theory of flow invariance. We are able to show the conditions under which the solutions of such a system are bounded being less restrictive than with the K-monotone theory, singular perturbation theory, or those based on supervised synaptic learning. We prove the existence and the uniqueness of the equilibrium. A strict Lyapunov function for the flow of a competitive neural system with different time scales is given, and based on it we are able to prove the global exponential stability of the equilibrium point." @default.
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- W2149018240 date "2005-04-05" @default.
- W2149018240 modified "2023-10-11" @default.
- W2149018240 title "Stability analysis of a self-organizing neural network with feedforward and feedback dynamics" @default.
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- W2149018240 doi "https://doi.org/10.1109/ijcnn.2004.1380176" @default.
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