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- YANG Zonghuang
- The Graduate School of Engineering, University of Tokushima
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- NISHIO Yoshifumi
- The Department of Electrical and Electronic Engineering, University
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- USHIDA Akio
- The Department of Electrical and Electronic Engineering, University
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説明
Cellular Neural Networks (CNNs) have been developed as a high-speed parallel signal-processing platform. In this paper, a generalized two-layer cellular neural network model is proposed for image processing, in which two templates are introduced between the two layers. We found from the simulations that the two-layer CNNs efficiently behave compared to the single-layer GNNs for the many applications of image processing. For examples, simulation problems such as linearly non-separable task-logic XOR, center point detection and object separation, etc. can be efficiently solved with the two-layer CNNs. The stability problems of the two-layer CNNs with symmetric and/or special coupling templates are also discussed based on the Lyapunov function technique. Its equilibrium points are found from the trajectories in a phase plane, whose results agree with those from simulations.
収録刊行物
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- IEICE transactions on fundamentals of electronics, communications and computer sciences
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IEICE transactions on fundamentals of electronics, communications and computer sciences 85 (9), 2052-2060, 2002-09-01
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詳細情報 詳細情報について
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- CRID
- 1571698602309973632
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- NII論文ID
- 110003209253
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- NII書誌ID
- AA10826239
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- ISSN
- 09168508
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- 本文言語コード
- en
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- データソース種別
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- CiNii Articles
