• DocumentCode
    1195005
  • Title

    Improvements of Complex-Valued Hopfield Associative Memory by Using Generalized Projection Rules

  • Author

    Donq-Liang Lee

  • Author_Institution
    Dept. of Inf. & Telecommun. Eng., Ming Chuan Univ., Taoyuan
  • Volume
    17
  • Issue
    5
  • fYear
    2006
  • Firstpage
    1341
  • Lastpage
    1347
  • Abstract
    In this letter, new design methods for the complex-valued multistate Hopfield associative memories (CVHAMs) are presented. We show that the well-known projection rule proposed by Personnaz can be generalized to complex domain such that the weight matrix of the CVHAM can be designed by using a simple and effective method. The stability of the proposed CVHAM is analyzed by using energy function approach which shows that in synchronous update mode the proposed model is guaranteed to converge to a fixed point from any given initial state. Moreover, the projection geometry of the generalized projection rule (GPR) is discussed. In order to enhance the recall capability, a strategy of eliminating the spurious memories is also reported. The validity and the performance of the proposed methods are investigated by computer simulation
  • Keywords
    Hopfield neural nets; content-addressable storage; stability; complex-valued multistate Hopfield associative memories; energy function method; generalized projection rules; projection geometry; stability; Associative memory; Computer simulation; Design methodology; Geometry; Ground penetrating radar; Neural networks; Neurons; Prototypes; Quantization; Stability analysis; Complex-valued Hopfield associative memory (CVHAM); generalized projection rule (GPR); spurious memory; Algorithms; Artificial Intelligence; Cluster Analysis; Computing Methodologies; Neural Networks (Computer); Pattern Recognition, Automated;
  • fLanguage
    English
  • Journal_Title
    Neural Networks, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1045-9227
  • Type

    jour

  • DOI
    10.1109/TNN.2006.878786
  • Filename
    1687943