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Cellular Neural Networks for Gray Image Noise Cancellation Based on a Hybrid Linear Matrix Inequality and Particle Swarm Optimization Approach

机译:基于混合线性矩阵不等式和粒子群算法的细胞神经网络灰度图像消噪

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摘要

This paper describes a technique for gray image noise cancellation. This method employs linear matrix inequality (LMI) and particle swarm optimization (PSO) based on cellular neural networks (CNN).We use two images that one is desired image and the other is corrupted to find the CNN template. The Lyapunov stability theorem is employed to derive the criterion for uniqueness and global asymptotic stability of the CNN equilibrium point. The current study characterizes the template design problem as a standard LMI problem and the optimization parameters of the templates are carried out by PSO. Finally, the examples are given to illustrate the effectiveness of the proposed method.
机译:本文介绍了一种用于消除灰度图像噪声的技术。该方法采用线性矩阵不等式(LMI)和基于细胞神经网络(CNN)的粒子群优化(PSO)。我们使用两张图像,其中一张是所需图像,另一张则损坏,以找到CNN模板。利用Lyapunov稳定性定理推导出CNN平衡点的唯一性和全局渐近稳定性的判据。当前的研究将模板设计问题描述为标准的LMI问题,并且模板的优化参数由PSO进行。最后,通过实例说明了该方法的有效性。

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  • 来源
    《Neural processing letters》 |2010年第2期|p.147-165|共19页
  • 作者单位

    Department of Electronic Engineering, National Kaohsiung University of Applied Sciences, Kaohsiung 807, Taiwan, ROC College of Information & Technology, Kun Shan University, Yung-Kong 71063, Taiwan, ROC;

    rnDepartment of Electronic Engineering, National Kaohsiung University of Applied Sciences, Kaohsiung 807, Taiwan, ROC;

    rnDepartment of Electronic Engineering, National Kaohsiung University of Applied Sciences, Kaohsiung 807, Taiwan, ROC;

    rnDepartment of Electronic Engineering, National Kaohsiung University of Applied Sciences, Kaohsiung 807, Taiwan, ROC;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    cellular neural networks; particle swarm optimization; linear matrix inequality; noise cancellation; image;

    机译:细胞神经网络粒子群优化;线性矩阵不等式噪音消除;图片;

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