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Paper Abstract and Keywords
Presentation 2022-08-02 09:25
Performance Evaluation of Time Series Forecasting with Chaotic Neural Network Reservoir using ReLU Derived Functions
Tatsuya Saito, Misa Fujita (Chukyo Univ.) NLP2022-27
Abstract (in Japanese) (See Japanese page) 
(in English) Reservoir computing has been attracting attention in recent years.
It can learn time-series data at high speed.
The chaotic neural network reservoir is one of the reservoir computing.
Its chaotic dynamics are expected to show high performance for processing time-series data.
In the original chaotic neural network reservoir, tanh or sigmoid function which requires a high computation cost is used as the activation function of neurons.
From this viewpoint, we proposed using other functions that require a small computation cost, such as ReLU, Leaky ReLU, tanh-approximate ReLU, and sigmoid-approximate ReLU as the activation function of neurons.
Also, we evaluate the performance of these chaotic neural network reservoirs for predicting time-series data.
Keyword (in Japanese) (See Japanese page) 
(in English) Chaotic Neural Network Reservoir / Reservoir Computing / Time Series Prediction / Machine Learning / / / /  
Reference Info. IEICE Tech. Rep., vol. 122, no. 143, NLP2022-27, pp. 7-10, Aug. 2022.
Paper # NLP2022-27 
Date of Issue 2022-07-26 (NLP) 
ISSN 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)
Download PDF NLP2022-27

Conference Information
Committee NLP  
Conference Date 2022-08-02 - 2022-08-02 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To NLP 
Conference Code 2022-08-NLP 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Performance Evaluation of Time Series Forecasting with Chaotic Neural Network Reservoir using ReLU Derived Functions 
Sub Title (in English)  
Keyword(1) Chaotic Neural Network Reservoir  
Keyword(2) Reservoir Computing  
Keyword(3) Time Series Prediction  
Keyword(4) Machine Learning  
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Keyword(6)  
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1st Author's Name Tatsuya Saito  
1st Author's Affiliation Chukyo University (Chukyo Univ.)
2nd Author's Name Misa Fujita  
2nd Author's Affiliation Chukyo University (Chukyo Univ.)
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Speaker Author-1 
Date Time 2022-08-02 09:25:00 
Presentation Time 25 minutes 
Registration for NLP 
Paper # NLP2022-27 
Volume (vol) vol.122 
Number (no) no.143 
Page pp.7-10 
#Pages 4 
Date of Issue 2022-07-26 (NLP) 

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