• DocumentCode
    821800
  • Title

    A bio-inspired two-layer mixed-signal flexible programmable chip for early vision

  • Author

    Galán, Ricardo Carmona ; Jiménez-Garrido, Francisco ; Domínguez-Castro, Rafael ; Espejo, Servando ; Roska, Tamás ; Rekeczky, Csaba ; Petrás, István ; Rodríguez-Vázquez, Ángel

  • Author_Institution
    Inst. de Microelectron., Campus de la Univ., Sevilla, Spain
  • Volume
    14
  • Issue
    5
  • fYear
    2003
  • Firstpage
    1313
  • Lastpage
    1336
  • Abstract
    A bio-inspired model for an analog programmable array processor (APAP), based on studies on the vertebrate retina, has permitted the realization of complex programmable spatio-temporal dynamics in VLSI. This model mimics the way in which images are processed in the visual pathway, what renders a feasible alternative for the implementation of early vision tasks in standard technologies. A prototype chip has been designed and fabricated in 0.5 μm CMOS. It renders a computing power per silicon area and power consumption that is amongst the highest reported for a single chip. The details of the bio-inspired network model, the analog building block design challenges and trade-offs and some functional tests results are presented in this paper.
  • Keywords
    CMOS logic circuits; VLSI; computer vision; neural chips; programmable logic arrays; CMOS; VLSI; analog programmable array processor; bio-inspired chip; cellular neural networks; early vision; machine vision; power consumption; programmable spatio-temporal dynamics; two-layer mixed-signal flexible programmable chip; vertebrate retina; visual pathway; CMOS technology; Cellular neural networks; Integrated circuit interconnections; Prototypes; Rendering (computer graphics); Retina; Semiconductor device modeling; Silicon; Spatiotemporal phenomena; Very large scale integration;
  • fLanguage
    English
  • Journal_Title
    Neural Networks, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1045-9227
  • Type

    jour

  • DOI
    10.1109/TNN.2003.816377
  • Filename
    1243730