This paper considers the Full-range (FR) model of Cellular Neural Networks (CNNs) in the case where the signal range is delimited by an ideal hard-limiter nonlinearity with two vertical segments in the i−v characteristic. A Łojasiewicz inequality around any equilibrium point, for a FRCNN with a symmetric interconnection matrix, is proved. It is also shown that the Łojasiewicz exponent is equal to 1/2. The main consequence is that any forward solution of a symmetric FRCNN has finite length and is exponentially convergent toward an equilibrium point, even in degenerate situations where the FRCNN possesses non-isolated equilibrium points. The obtained results are shown to improve the previous results in literature on convergence or almost convergence of symmetric FRCNNs.
DI MARCO, M., Forti, M., Grazzini, M., Pancioni, L. (2012). Lojasiewicz inequality and exponential convergence of the full-range model of CNNs. INTERNATIONAL JOURNAL OF CIRCUIT THEORY AND APPLICATIONS, 40, 409-419 [10.1002/cta.717].
Lojasiewicz inequality and exponential convergence of the full-range model of CNNs
DI MARCO, MAURO;FORTI, MAURO;GRAZZINI, MASSIMO;PANCIONI, LUCA
2012-01-01
Abstract
This paper considers the Full-range (FR) model of Cellular Neural Networks (CNNs) in the case where the signal range is delimited by an ideal hard-limiter nonlinearity with two vertical segments in the i−v characteristic. A Łojasiewicz inequality around any equilibrium point, for a FRCNN with a symmetric interconnection matrix, is proved. It is also shown that the Łojasiewicz exponent is equal to 1/2. The main consequence is that any forward solution of a symmetric FRCNN has finite length and is exponentially convergent toward an equilibrium point, even in degenerate situations where the FRCNN possesses non-isolated equilibrium points. The obtained results are shown to improve the previous results in literature on convergence or almost convergence of symmetric FRCNNs.File | Dimensione | Formato | |
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https://hdl.handle.net/11365/26505
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