Analog VLSI circuit implementation. of an adaptive neuromorphic olfaction chip

Thomas Jacob Koickal*, Alister Hamilton, Su Lim Tan, James A. Covington, Julian W. Gardner, Tim C. Pearce

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

In this paper, we present the analog circuit design and implementation of the components of an adaptive neuromorphic olfaction chip. A chemical sensor array employing carbon black composite sensing materials with integrated signal processing circuitry forms the front end of the chip. The sensor signal processing circuitry includes a dc offset cancellation circuit to ameliorate loss of measurement range associated with chemical sensors. Drawing inspiration from biological olfactory systems, the analog circuits used to process signals from the on-chip odor sensors make use of temporal "spiking" signals to act as carriers of odor information. An on-chip spike time dependent learning circuit is integrated to dynamically adapt weights for odor detection and classification. All the component subsystems implemented on chip have been successfully tested in silicon.

Original languageEnglish
Pages (from-to)60-73
Number of pages14
JournalIEEE Transactions on Circuits and Systems Part 1 Fundamental Theory and Applications
Volume54
Issue number1
DOIs
Publication statusPublished - Jan 2007
EventIEEE International Symposium on Circuits and Systems (ISCAS) - Kobe, Japan
Duration: 23 May 200526 May 2005

Keywords

  • analog VLSI
  • electronic nose
  • machine olfaction
  • neuromorphic circuits
  • on-chip learning
  • spike-timing-dependent plasticity (STDP)
  • DEPENDENT SYNAPTIC PLASTICITY
  • SENSOR ARRAY
  • SYNAPSES
  • NEURONS
  • SILICON
  • DEPRESSION
  • BULB

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