Asic design of a kohonen neural network microchip
This paper discusses the Kohonen neural network (KNN) processor and its KNN computation engine microchip. The ASIC design of the KNN processor adopts a novel implementation approach whereby the computation of the KNN algorithm is performed on the custom ASIC microchip and its operations are governed...
Saved in:
Main Authors: | , |
---|---|
Format: | Book Section |
Language: | English |
Published: |
IEEE
2004
|
Subjects: | |
Online Access: | http://eprints.utm.my/id/eprint/2031/1/RajahKhalilHani2004__ASICDesignKohonenNeuralNetwork.pdf http://eprints.utm.my/id/eprint/2031/ http://dx.doi.org/10.1109/SMELEC.2004.1620857 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
id |
my.utm.2031 |
---|---|
record_format |
eprints |
spelling |
my.utm.20312013-12-18T03:29:54Z http://eprints.utm.my/id/eprint/2031/ Asic design of a kohonen neural network microchip Rajah, Avinash Hani, Mohamed Khalil TK Electrical engineering. Electronics Nuclear engineering This paper discusses the Kohonen neural network (KNN) processor and its KNN computation engine microchip. The ASIC design of the KNN processor adopts a novel implementation approach whereby the computation of the KNN algorithm is performed on the custom ASIC microchip and its operations are governed by a FPGA based controller. Thus, the ASIC implementation of the KNN processor is derived through integration between a custom ASIC and FPGA. The 3.3V AMI 0.5um CO5M-D process technology was used to achieve the VLSI design of the computation engine microchip and the entire design adopted the BBX cell based methodology, which is a viable alternative to conventional ASIC methodology. IEEE 2004-12-07 Book Section PeerReviewed application/pdf en http://eprints.utm.my/id/eprint/2031/1/RajahKhalilHani2004__ASICDesignKohonenNeuralNetwork.pdf Rajah, Avinash and Hani, Mohamed Khalil (2004) Asic design of a kohonen neural network microchip. In: Proceedings ICSE 2004 - 2004 IEEE International Conference on Semiconductor Electronics. IEEE, USA, pp. 148-151. http://dx.doi.org/10.1109/SMELEC.2004.1620857 DOI:10.1109/SMELEC.2004.1620857 |
institution |
Universiti Teknologi Malaysia |
building |
UTM Library |
collection |
Institutional Repository |
continent |
Asia |
country |
Malaysia |
content_provider |
Universiti Teknologi Malaysia |
content_source |
UTM Institutional Repository |
url_provider |
http://eprints.utm.my/ |
language |
English |
topic |
TK Electrical engineering. Electronics Nuclear engineering |
spellingShingle |
TK Electrical engineering. Electronics Nuclear engineering Rajah, Avinash Hani, Mohamed Khalil Asic design of a kohonen neural network microchip |
description |
This paper discusses the Kohonen neural network (KNN) processor and its KNN computation engine microchip. The ASIC design of the KNN processor adopts a novel implementation approach whereby the computation of the KNN algorithm is performed on the custom ASIC microchip and its operations are governed by a FPGA based controller. Thus, the ASIC implementation of the KNN processor is derived through integration between a custom ASIC and FPGA. The 3.3V AMI 0.5um CO5M-D process technology was used to achieve the VLSI design of the computation engine microchip and the entire design adopted the BBX cell based methodology, which is a viable alternative to conventional ASIC methodology. |
format |
Book Section |
author |
Rajah, Avinash Hani, Mohamed Khalil |
author_facet |
Rajah, Avinash Hani, Mohamed Khalil |
author_sort |
Rajah, Avinash |
title |
Asic design of a kohonen neural network microchip |
title_short |
Asic design of a kohonen neural network microchip |
title_full |
Asic design of a kohonen neural network microchip |
title_fullStr |
Asic design of a kohonen neural network microchip |
title_full_unstemmed |
Asic design of a kohonen neural network microchip |
title_sort |
asic design of a kohonen neural network microchip |
publisher |
IEEE |
publishDate |
2004 |
url |
http://eprints.utm.my/id/eprint/2031/1/RajahKhalilHani2004__ASICDesignKohonenNeuralNetwork.pdf http://eprints.utm.my/id/eprint/2031/ http://dx.doi.org/10.1109/SMELEC.2004.1620857 |
_version_ |
1643643480735481856 |
score |
13.211869 |