Paper Abstract and Keywords |
Presentation |
2020-01-24 13:25
Design of sparse filters using a neural network Taro Itani, Masayoshi Nakamoto (Hiroshima Univ.), Naoyuki Aikawa (Tokyo univ. of science) IT2019-75 SIP2019-88 RCS2019-305 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
A sparse filter is a digital filter that contains zero coefficients. By designing a sparse filter with a redundant filter order, a higher-performance filter can be designed than a low-order nonsparse filter with the same number of multipliers. In the design of sparse filters, it can be regarded as a combinatorial optimization problem of selecting which coefficient is 0. In order to solve this problem, a huge amount of calculation time is required. Therefore, this study proposes a sparse filter design method based on a neural network using sparse filters designed in advance as learning data. It is confirmed that the performance of the designed sparse filter can be improved by increasing the number of training data by this design method. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
disital filters / sparsity / neural network / / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 119, no. 377, SIP2019-88, pp. 227-232, Jan. 2020. |
Paper # |
SIP2019-88 |
Date of Issue |
2020-01-16 (IT, SIP, RCS) |
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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IT2019-75 SIP2019-88 RCS2019-305 |
Conference Information |
Committee |
IT SIP RCS |
Conference Date |
2020-01-23 - 2020-01-24 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Hiroshima City Youth Center |
Topics (in Japanese) |
(See Japanese page) |
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Paper Information |
Registration To |
SIP |
Conference Code |
2020-01-IT-SIP-RCS |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Design of sparse filters using a neural network |
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disital filters |
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sparsity |
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neural network |
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1st Author's Name |
Taro Itani |
1st Author's Affiliation |
Hiroshima University (Hiroshima Univ.) |
2nd Author's Name |
Masayoshi Nakamoto |
2nd Author's Affiliation |
Hiroshima University (Hiroshima Univ.) |
3rd Author's Name |
Naoyuki Aikawa |
3rd Author's Affiliation |
Tokyo university of science (Tokyo univ. of science) |
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Speaker |
Author-1 |
Date Time |
2020-01-24 13:25:00 |
Presentation Time |
25 minutes |
Registration for |
SIP |
Paper # |
IT2019-75, SIP2019-88, RCS2019-305 |
Volume (vol) |
vol.119 |
Number (no) |
no.376(IT), no.377(SIP), no.378(RCS) |
Page |
pp.227-232 |
#Pages |
6 |
Date of Issue |
2020-01-16 (IT, SIP, RCS) |
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