Towards an analogue neuromorphic VLSI instrument for the sensing of complex odours
Almost all electronic nose instruments reported today employ pattern recognition algorithms written in software and run on digital processors, e.g. micro-processors, microcontrollers or FPGAs. Conversely, in this paper we describe the analogue VLSI implementation of an electronic nose through the de...
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American Institute of Physics
2011
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my.utm.301042017-02-04T07:27:06Z http://eprints.utm.my/id/eprint/30104/ Towards an analogue neuromorphic VLSI instrument for the sensing of complex odours Che Harun, Fauzan Khairi Ab. Aziz, Muhammad Fazli Covington, James A. Gardner, Julian W. TK Electrical engineering. Electronics Nuclear engineering Almost all electronic nose instruments reported today employ pattern recognition algorithms written in software and run on digital processors, e.g. micro-processors, microcontrollers or FPGAs. Conversely, in this paper we describe the analogue VLSI implementation of an electronic nose through the design of a neuromorphic olfactory chip. The modelling, design and fabrication of the chip have already been reported. Here a smart interface has been designed and characterised for thisneuromorphic chip. Thus we can demonstrate the functionality of the a VLSI neuromorphic chip, producing differing principal neuron firing patterns to real sensor response data. Further work is directed towards integrating 9 separate neuromorphic chips to create a large neuronal network to solve more complex olfactory problems. American Institute of Physics 2011 Book Section PeerReviewed Che Harun, Fauzan Khairi and Ab. Aziz, Muhammad Fazli and Covington, James A. and Gardner, Julian W. (2011) Towards an analogue neuromorphic VLSI instrument for the sensing of complex odours. In: Olfaction And Electronic Nose: Proceedings of the 14th International Symposium on Olfaction and Electronic Nose Date: 2-5 May 2011. American Institute of Physics, New York City, NY, (USA), pp. 223-224. ISBN 978-073540920-0 http://dx.doi.org/10.1063/1.3626367 10.1063/1.3626367 |
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TK Electrical engineering. Electronics Nuclear engineering Che Harun, Fauzan Khairi Ab. Aziz, Muhammad Fazli Covington, James A. Gardner, Julian W. Towards an analogue neuromorphic VLSI instrument for the sensing of complex odours |
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Almost all electronic nose instruments reported today employ pattern recognition algorithms written in software and run on digital processors, e.g. micro-processors, microcontrollers or FPGAs. Conversely, in this paper we describe the analogue VLSI implementation of an electronic nose through the design of a neuromorphic olfactory chip. The modelling, design and fabrication of the chip have already been reported. Here a smart interface has been designed and characterised for thisneuromorphic chip. Thus we can demonstrate the functionality of the a VLSI neuromorphic chip, producing differing principal neuron firing patterns to real sensor response data. Further work is directed towards integrating 9 separate neuromorphic chips to create a large neuronal network to solve more complex olfactory problems. |
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Book Section |
author |
Che Harun, Fauzan Khairi Ab. Aziz, Muhammad Fazli Covington, James A. Gardner, Julian W. |
author_facet |
Che Harun, Fauzan Khairi Ab. Aziz, Muhammad Fazli Covington, James A. Gardner, Julian W. |
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Che Harun, Fauzan Khairi |
title |
Towards an analogue neuromorphic VLSI instrument for the sensing of complex odours |
title_short |
Towards an analogue neuromorphic VLSI instrument for the sensing of complex odours |
title_full |
Towards an analogue neuromorphic VLSI instrument for the sensing of complex odours |
title_fullStr |
Towards an analogue neuromorphic VLSI instrument for the sensing of complex odours |
title_full_unstemmed |
Towards an analogue neuromorphic VLSI instrument for the sensing of complex odours |
title_sort |
towards an analogue neuromorphic vlsi instrument for the sensing of complex odours |
publisher |
American Institute of Physics |
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2011 |
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http://eprints.utm.my/id/eprint/30104/ http://dx.doi.org/10.1063/1.3626367 |
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13.211869 |