A 0.8-μm CMOS two-dimensional programmable mixed-signal focal-plane array processor with on-chip binary imaging and instructions storage

Rafael Domínguez-Castro, Servando Espejo, Angel Rodríguez-Vázquez, Ricardo A. Carmona, Péter Földesy, Ákos Zarándy, Péter Szolgay, Tamás Szirányi, Tamás Roska

Research output: Contribution to journalArticle

123 Citations (Scopus)

Abstract

This paper presents a CMOS chip for the parallel acquisition and concurrent analog processing of two-dimensional (2-D) binary images. Its processing function is determined by a reduced set of 19 analog coefficients whose values are programmable with 7-b accuracy. The internal programming signals are analog, but the external control interface is fully digital. Onchip nonlinear digital-to-analog converters (DAC's) map digitally coded weight values into analog control signals, using feedback to predistort their transfer characteristics in accordance to the response of the analog programming circuitry. This strategy cancels out the nonlinear dependence of the analog circuitry with the programming signal and reduces the influence of interchip technological parameters random fluctuations. The chip includes a small digital RAM memory to store eight sets of processing parameters in the periphery of the cell array and four 2-D binary images spatially distributed over the processing array. It also includes the necessary control circuitry to realize the stored instructions in any order and also to realize programmable logic operations among images. The chip architecture is based on the cellular neural/nonlinear network universal machine (CNN-UM). It has been fabricated in a 0.8-μm single-poly double-metal technology and features 2-μs operation speed (time required to process an image) and around 7-b accuracy in the analog processing operations.

Original languageEnglish
Pages (from-to)1013-1025
Number of pages13
JournalIEEE Journal of Solid-State Circuits
Volume32
Issue number7
DOIs
Publication statusPublished - Jul 1 1997

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Keywords

  • Analog array processors
  • Cellular neural networks
  • Focal plane processors
  • Vision chips

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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