• DocumentCode
    1797256
  • Title

    Case study of Zhang matrix inverse for different ZFs leading to different nets

  • Author

    Dongsheng Guo ; Binbin Qiu ; Zhende Ke ; Zhi Yang ; Yunong Zhang

  • Author_Institution
    Sch. of Inf. Sci. & Technol., Sun Yat-sen Univ., Guangzhou, China
  • fYear
    2014
  • fDate
    6-11 July 2014
  • Firstpage
    2764
  • Lastpage
    2769
  • Abstract
    This paper primarily demonstrates the effectiveness of the Z-type methodology for solving the problem of time-variant matrix inverse (termed Zhang matrix inverse, ZMI). As a case study of ZMI with examples, the online solution of ZMI is investigated in this paper. Specifically, different Zhang functions (ZFs), which lead to different effective Z-type models (i.e., Zhang neural nets), are proposed and implemented as the error basis functions for ZMI. Meanwhile, a specific relationship between the Z-type model and others´ model/method [i.e., the Getz and Marsden (G-M) dynamic system] is presented. Eventually, the MATLAB Simulink modeling and simulative verifications with examples using such different Z-type models are further researched. Both theoretical analysis and modeling results demonstrate the efficacy of the proposed Z-type models which originate from different ZFs for ZMI.
  • Keywords
    mathematics computing; matrix inversion; recurrent neural nets; MATLAB Simulink modeling; Z-type methodology; Z-type models; ZMI; Zhang functions; Zhang matrix inverse; Zhang neural net; error basis functions; recurrent neural net; time-variant matrix inverse; Analytical models; Convergence; Equations; Integrated circuit modeling; MATLAB; Mathematical model;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks (IJCNN), 2014 International Joint Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4799-6627-1
  • Type

    conf

  • DOI
    10.1109/IJCNN.2014.6889367
  • Filename
    6889367