• DocumentCode
    3544603
  • Title

    A built-in self-test design with low power consumption based on genetic algorithm

  • Author

    Tan, Enmin ; Wang, Li

  • Author_Institution
    Sch. of Electron. Eng., Guilin Univ. of Electron. Technol., Guilin, China
  • fYear
    2009
  • fDate
    16-19 Aug. 2009
  • Abstract
    A low peak power consumption built-in self-test (BIST) design based on genetic algorithm (GA), which is denoted by GAITPG, has been proposed in our previous study. This paper presents an improved performance of GAITPG, which also aims at the reduction of the changes between successive test patterns. (m-1) vectors were inserted between two successive n-bit pseudorandom test patterns generated by the original linear feedback shifted register (LFSR), while m and the element of groups were optimized by GA. Experimental results based on ISCAS´85 benchmark circuits show that the test pattern generator (TPG) with low power consumption proposed in this paper is efficient, without losing stuck-at fault coverage. Also, a comparison of reduction of power consumption between GAITPG and other scheme (such as inserted TPG (ITPG)) was reported.
  • Keywords
    benchmark testing; built-in self test; circuit feedback; genetic algorithms; low-power electronics; random number generation; shift registers; (m-1) vectors; GAITPG; ISCAS´85 benchmark circuits; built-in self-test design; genetic algorithm; linear feedback shifted register; low peak power consumption; n-bit pseudorandom test patterns; stuck-at fault coverage; test pattern generator; Algorithm design and analysis; Benchmark testing; Built-in self-test; Circuit testing; Energy consumption; Feedback circuits; Genetic algorithms; Registers; Test pattern generators; Vectors; BIST; GA; LFSR; TPG; low power consumption design; weighted switching activity (WSA);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electronic Measurement & Instruments, 2009. ICEMI '09. 9th International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4244-3863-1
  • Electronic_ISBN
    978-1-4244-3864-8
  • Type

    conf

  • DOI
    10.1109/ICEMI.2009.5274527
  • Filename
    5274527