• DocumentCode
    2064352
  • Title

    COGENT: COmpressing and compacting GEnetic algorithms and Neural networks based automatic Test generator

  • Author

    Shara, Shekhar Agrawal

  • Author_Institution
    Bradley Dept. of Electr. & Comput. Eng., Virginia Polytech. & State Univ., Blacksburg, VA, USA
  • fYear
    2003
  • fDate
    23-25 June 2003
  • Firstpage
    103
  • Lastpage
    107
  • Abstract
    Genetic algorithms are one of the most powerful tools used in the field of testing to deliver high-quality automatic test pattern generation (ATPG) for both sequential and combinational circuits essentially because ATPG is a search and optimization problem. Artificial neural networks, using the learning methodology can be used to solve any class of linearly non-separable problems, which includes classification and recognition. In this paper, these two tools have been combined to deliver a high performance ATPG, COGENT. COGENT also compacts and compresses/decompresses data. The compression algorithm used is a variation of the Coulomb´s scheme. The results for all the different cases examined have been tabulated and discussed.
  • Keywords
    automatic test pattern generation; combinational circuits; data compression; genetic algorithms; learning (artificial intelligence); linear programming; neural nets; search problems; sequential circuits; COGENT; Coulomb scheme variation; artificial neural network; automatic test pattern generator; classification; combinational circuit; compression algorithm; data compression; data decompression; deterministic method; genetic algorithm; high performance ATPG; learning methodology; linearly nonseparable problem; optimization problem; recognition; search problem; sequential circuit; Artificial neural networks; Automatic test pattern generation; Automatic testing; Circuit faults; Circuit testing; Fault detection; Genetic algorithms; Neural networks; Sequential analysis; Test pattern generators;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Soft Computing in Industrial Applications, 2003. SMCia/03. Proceedings of the 2003 IEEE International Workshop on
  • Print_ISBN
    0-7803-7855-5
  • Type

    conf

  • DOI
    10.1109/SMCIA.2003.1231352
  • Filename
    1231352