CNO-LSTM: A Chaotic Neural Oscillatory Long Short-Term Memory Model for Text Classification-Reference-Cited by-同舟云学术

CNO-LSTM: A Chaotic Neural Oscillatory Long Short-Term Memory Model for Text Classification

Published:2022 Issue: Volume:10 Page:129564-129579
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Shi Nuobei¹^ORCID,Chen Zhuohui²^ORCID,Chen Ling³,Lee Raymond S. T.¹^ORCID

Affiliation:

1. Faculty of Science and Technology, Beijing Normal University–Hong Kong Baptist University United International College, Zhuhai, China

2. Faculty of Innovation Engineering, Macau University of Science and Technology, Taipa, Macau, China

3. School of Applied Science and Civil Engineering, Beijing Institute of Technology Zhuhai, Zhuhai, China

Funder

Beijing Normal University–Hong Kong Baptist University United International College

Key Laboratory for Artificial Intelligence and Multi-Model Data Processing of Department of Education of Guangdong Province

Science and Technology Commissioner Project of Research on Offline Handwritten Signature Verification from the Department of Science and Technology of Guangdong Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/9668973/09982464.pdf?arnumber=9982464

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4. Multi-Timescale Long Short-Term Memory Neural Network for Modelling Sentences and Documents

5. Long short-term memory over recursive structures;zhu;Proc 32nd Int Conf Mach Learn (ICML),2015

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