Image Processing of Two-Layer CNNs : Applications and Their Stability

被引用文献1件 参考文献31件
  • YANG Zonghuang
    The Graduate School of Engineering, University of Tokushima
  • NISHIO Yoshifumi
    The Department of Electrical and Electronic Engineering, University
  • USHIDA Akio
    The Department of Electrical and Electronic Engineering, University

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抄録

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.

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詳細情報 詳細情報について

  • CRID
    1571698602309973632
  • NII論文ID
    110003209253
  • NII書誌ID
    AA10826239
  • ISSN
    09168508
  • 本文言語コード
    en
  • データソース種別
    • CiNii Articles

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