Paper Abstract and Keywords |
Presentation |
2009-09-25 11:00
Associative-Memory-Based LSI Architecture with Automatic Learning Functionality and Application to Handwritten-Character Recognition Wataru Imafuku, Tania Ansari, Akio Kawabata, Hans Juergen Mattausch, Tetsushi Koide (Hiroshima Univ.) CAS2009-40 NLP2009-76 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
n the presented research on VLSI-system design for handwritten-character learning and recognition, an associative memory architecture for searching the most similar data among previously stored reference data is applied.
The chosen associative memory achieves high speed, low power consumption and small implementation area due to a mixed digital-analog fully-parallel nearest-match search circuitry.
To recognize new data, a learning capability based on the concept of a short/long-term memory which tries to mimic the function of the human brain is realized.
For improvement of the recognition rate, we propose a reference-data-optimization algorithm that averages the recognized input patterns for each stored reference object and updates the corresponding reference pattern periodically.
We evaluated the proposed intelligent VLSI-design method for the application of hand-written character learning and recognition.
Therefore, test-chip in ${0.18}$ ${{\mu}m}$ CMOS technology was designed to demonstrate the proposed algorithm and design method.
The simulated processing capability of this test-chip amounts to \mbox{0.3 million} input-character images per second. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Associative memory / Automatic learning / Short/long-term memory / Handwritten-character recognition / Reference-data optimization / / / |
Reference Info. |
IEICE Tech. Rep., vol. 109, no. 199, CAS2009-40, pp. 91-96, Sept. 2009. |
Paper # |
CAS2009-40 |
Date of Issue |
2009-09-17 (CAS, NLP) |
ISSN |
Print edition: ISSN 0913-5685 Online edition: ISSN 2432-6380 |
Copyright and reproduction |
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) |
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CAS2009-40 NLP2009-76 |
Conference Information |
Committee |
CAS NLP |
Conference Date |
2009-09-24 - 2009-09-25 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Hiroshima Univ. Higashi Senda Campus |
Topics (in Japanese) |
(See Japanese page) |
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Paper Information |
Registration To |
CAS |
Conference Code |
2009-09-CAS-NLP |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Associative-Memory-Based LSI Architecture with Automatic Learning Functionality and Application to Handwritten-Character Recognition |
Sub Title (in English) |
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Keyword(1) |
Associative memory |
Keyword(2) |
Automatic learning |
Keyword(3) |
Short/long-term memory |
Keyword(4) |
Handwritten-character recognition |
Keyword(5) |
Reference-data optimization |
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1st Author's Name |
Wataru Imafuku |
1st Author's Affiliation |
Hiroshima University (Hiroshima Univ.) |
2nd Author's Name |
Tania Ansari |
2nd Author's Affiliation |
Hiroshima University (Hiroshima Univ.) |
3rd Author's Name |
Akio Kawabata |
3rd Author's Affiliation |
Hiroshima University (Hiroshima Univ.) |
4th Author's Name |
Hans Juergen Mattausch |
4th Author's Affiliation |
Hiroshima University (Hiroshima Univ.) |
5th Author's Name |
Tetsushi Koide |
5th Author's Affiliation |
Hiroshima University (Hiroshima Univ.) |
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Speaker |
Author-1 |
Date Time |
2009-09-25 11:00:00 |
Presentation Time |
25 minutes |
Registration for |
CAS |
Paper # |
CAS2009-40, NLP2009-76 |
Volume (vol) |
vol.109 |
Number (no) |
no.199(CAS), no.200(NLP) |
Page |
pp.91-96 |
#Pages |
6 |
Date of Issue |
2009-09-17 (CAS, NLP) |
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