• DocumentCode
    483236
  • Title

    A Novel FPGA Mathematical Technology Based AI-Fuzzy VCN Algorithm of Automation

  • Author

    Zhang Ting-Fang ; Ye Qiu-Sun

  • Author_Institution
    Dept. of Econ. & Math., Wuyi Univ., Wuyishan
  • fYear
    2009
  • fDate
    23-25 Jan. 2009
  • Firstpage
    323
  • Lastpage
    326
  • Abstract
    Field programmable gate array (FPGA) was a new material programmable logic units in end of the 20th century, FPGA was with some properties such that, large memory of capacities, short delays of time, improvement able & flexibilities etc. On the basis theory of neural fuzzy system of Networks (NFSN), this paper gives a FPGA method of DNMA (Dynamic Numbers Measuring Algorithm) with VCN (Variable Carrying Numbers). The algorithm takes a reusing technique of VCR (Variable Carrying Rules) path, a process of middle-data to be shaped & placed in RAM. In the deep research & analysis of testing, this algorithm is practicable.
  • Keywords
    field programmable gate arrays; fuzzy neural nets; fuzzy set theory; fuzzy systems; mathematics computing; random-access storage; AI-Fuzzy VCN algorithm; FPGA mathematical technology; dynamic numbers measuring algorithm; field programmable gate array; fuzzy set; neural fuzzy system; random access memory; variable carrying number; variable carrying rules path; Algorithm design and analysis; Automation; Delay effects; Field programmable gate arrays; Fuzzy systems; Heuristic algorithms; Programmable logic arrays; Read-write memory; Testing; Video recording; Dynamic Numbers Measuring Algorithm (DNMA); Field Programmable Gate Array (FPGA); Neural Fuzzy System of Networks (NFSN); Variable Carrying Numbers (VCN); Variable Carrying Rules (VCR).;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Knowledge Discovery and Data Mining, 2009. WKDD 2009. Second International Workshop on
  • Conference_Location
    Moscow
  • Print_ISBN
    978-0-7695-3543-2
  • Type

    conf

  • DOI
    10.1109/WKDD.2009.172
  • Filename
    4771942