• DocumentCode
    3394760
  • Title

    An encoder for vector quantization neural networks

  • Author

    Ancona, Fabio ; Rovetta, Stefano ; Zunino, Rodolfo

  • Author_Institution
    Dept. of Biophys. & Electron. Eng., Genoa Univ., Italy
  • Volume
    2
  • fYear
    1997
  • fDate
    3-6 Aug. 1997
  • Firstpage
    1286
  • Abstract
    Large-scale parallelism and analog computation are exploited to obtain a neural module, suitable for both functioning and training, since appropriate signal lines are provided. The VQ encoder is self-contained and therefore can be embedded into any system, either analog or digital. It implements efficiently the vector matching operations, therefore it can be exploited in systems based on any vector quantization algorithm, with good throughput.
  • Keywords
    VLSI; analogue processing circuits; neural chips; vector quantisation; VLSI; analog computation; embedded system; large-scale parallelism; neural module; signal lines; throughput; vector matching operations; vector quantization neural networks; Biophysics; Circuits; Large-scale systems; Neural networks; Neurons; Parallel processing; Prototypes; Throughput; Vector quantization; Very large scale integration;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Circuits and Systems, 1997. Proceedings of the 40th Midwest Symposium on
  • Print_ISBN
    0-7803-3694-1
  • Type

    conf

  • DOI
    10.1109/MWSCAS.1997.662316
  • Filename
    662316