Growing Echo State Network With an Inverse-Free Weight Update Strategy-Reference-Cited by-同舟云学术

Growing Echo State Network With an Inverse-Free Weight Update Strategy

Published:2023-02 Issue:2 Volume:53 Page:753-764
ISSN:2168-2267
Container-title:IEEE Transactions on Cybernetics
language:
Short-container-title:IEEE Trans. Cybern.

Author:

Chen Xiufang¹^ORCID,Luo Xin²^ORCID,Jin Long¹^ORCID,Li Shuai¹^ORCID,Liu Mei¹^ORCID

Affiliation:

1. School of Information Science and Engineering, Lanzhou University, Lanzhou, China

2. Chongqing Key Laboratory of Big Data and Intelligent Computing, Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing, China

Funder

National Natural Science Foundation of China

Natural Science Foundation of Gansu Province

Team Project of Natural Science Foundation of Qinghai Province China

Gansu Provincial Youth Doctoral Fund of Colleges and Universities

Fundamental Research Funds for the Central Universities

Supercomputing Center of Lanzhou University

Natural Science Foundation of Chongqing

CAAI Huawei MindSpore Open Fund

Pioneer Hundred Talents Program of Chinese Academy of Sciences

Special Projects of the Central Government in Guidance of Local Science and Technology Development

Science and Technology Project of Chengguan District of Lanzhou

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Human-Computer Interaction,Information Systems,Control and Systems Engineering,Software

Link

http://xplorestaging.ieee.org/ielx7/6221036/10016773/09740037.pdf?arnumber=9740037

Reference54 articles.

1. A Novel Neurodynamic Approach to Constrained Complex-Variable Pseudoconvex Optimization

2. Multi-timescale Forecast of Solar Irradiance Based on Multi-task Learning and Echo State Network Approaches

3. Stacked Broad Learning System: From Incremental Flatted Structure to Deep Model

4. Broad learning system: A new learning paradigm and system without going deep

5. Broad Learning System: An Effective and Efficient Incremental Learning System Without the Need for Deep Architecture

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