Robustness of delta operator based cellular neural networks

The delta operator approach to continuous-time cellular neural networks (CT-CNNs) is investigated in terms of a robust realization. It is shown that earlier results concerning the robustness of CT-CNNs can be obtained as a limiting case of this approach, while at the same time, this allows us to for...

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Hauptverfasser:	Mirzai, B., Reddy, H.C., Moschytz, G.S.
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Cellular neural networks Computer networks Image processing Information processing Laboratories Limiting Nonlinear equations Robustness Sampling methods Signal processing
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creator	Mirzai, B. Reddy, H.C. Moschytz, G.S.
description	The delta operator approach to continuous-time cellular neural networks (CT-CNNs) is investigated in terms of a robust realization. It is shown that earlier results concerning the robustness of CT-CNNs can be obtained as a limiting case of this approach, while at the same time, this allows us to formulate robustness considerations for discrete-time CNNs.
doi_str_mv	10.1109/ISCAS.1997.609006
format	Conference Proceeding
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source	IEEE Electronic Library (IEL) Conference Proceedings
subjects	Cellular neural networks Computer networks Image processing Information processing Laboratories Limiting Nonlinear equations Robustness Sampling methods Signal processing
title	Robustness of delta operator based cellular neural networks
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