In a series of papers published in the seventies, Grossberg has developed a geometric approach for analyzing the global dynamical behavior and convergence properties of a class of competitive dynamical systems. In this paper, Grossberg approach is extended to competitive standard cellular neural networks (CNNs), and it is used to investigate convergence of classes of non-symmetric competitive CNNs under the hypothesis that they induce a globally consistent decision scheme.
DI MARCO, M., Forti, M., Grazzini, M., Nistri, P., Pancioni, L. (2007). A Study on Convergence of Competitive CNNs. In IEEE International Symposium on Circuits and Systems, 2007. ISCAS 2007. (pp.3155-3158) [10.1109/ISCAS.2007.378100].
A Study on Convergence of Competitive CNNs
DI MARCO, MAURO;FORTI, MAURO;NISTRI, PAOLO;PANCIONI, LUCA
2007-01-01
Abstract
In a series of papers published in the seventies, Grossberg has developed a geometric approach for analyzing the global dynamical behavior and convergence properties of a class of competitive dynamical systems. In this paper, Grossberg approach is extended to competitive standard cellular neural networks (CNNs), and it is used to investigate convergence of classes of non-symmetric competitive CNNs under the hypothesis that they induce a globally consistent decision scheme.
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https://hdl.handle.net/11365/25694
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