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

1 Citations 31 References
  • 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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Description

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.

Journal

  • IEICE Trans. Fundamentals

    IEICE Trans. Fundamentals 85 (9), 2052-2060, 2002-09-01

    The Institute of Electronics, Information and Communication Engineers

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Keywords

Details 詳細情報について

  • CRID
    1571698602309973632
  • NII Article ID
    110003209253
  • NII Book ID
    AA10826239
  • ISSN
    09168508
  • Text Lang
    en
  • Data Source
    • CiNii Articles

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