A New Sufficient Condition on the Complete Stability of a Class Cellular Neural Networks

  • Li-qun Zhou
  • Guang-da Hu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3971)


In this paper, a sufficient condition is presented to ensure the complete stability of a cellular neural networks (CNNs) that output functions are a set of piecewise sigmoid nonlinear functions. The convergence theorem of the Gauss-Seidel method and Gauss-Seidel method, which is an iterative technique for solving a linear algebraic equation, plays an important role in our discussion.


Linear Algebraic Equation Comparison Matrix Cellular Neural Network Zero Vector Iterative Technique 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Li-qun Zhou
    • 1
    • 2
  • Guang-da Hu
    • 1
  1. 1.Department of Control Science and EngineeringHarbin Institute of TechnologyHarbinP.R. China
  2. 2.Department of MathematicsQiQihar UniversityQiQiharP.R. China

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