Comprehensive Study on Zeroing Neural Network With High-Order Evolutionary Formula, Nonlinear Functions, and Variable Parameter for Time-Changing Matrix Cholesky Decomposition-Reference-Cited by-同舟云学术

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Comprehensive Study on Zeroing Neural Network With High-Order Evolutionary Formula, Nonlinear Functions, and Variable Parameter for Time-Changing Matrix Cholesky Decomposition

Published:2024-06 Issue:6 Volume:54 Page:3642-3651
ISSN:2168-2216
Container-title:IEEE Transactions on Systems, Man, and Cybernetics: Systems
language:
Short-container-title:IEEE Trans. Syst. Man Cybern, Syst.

Author:

Xiao Lin¹^ORCID,Xiao Sida¹,He Yongjun¹^ORCID,Dai Jianhua¹^ORCID,Wang Yaonan²^ORCID,Li Yiwei³

Affiliation:

1. Hunan Provincial Key Laboratory of Intelligent Computing and Language Information Processing, Hunan Normal University, Changsha, China

2. College of Electric and Information Technology, Hunan University, Changsha, China

3. College of Computer, National University of Defense Technology, Changsha, China

Funder

Natural Science Foundation of Hunan Province of China

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6221021/10532208/10477436.pdf?arnumber=10477436

Reference49 articles.

1. Matrix Factorization Techniques for Recommender Systems

2. Online learning for matrix factorization and sparse coding;Mairal;J. Mach. Learn. Res.,2010

3. Computation of generalized inverses by using the LDL∗ decomposition

4. A fast algorithm for solving tridiagonal quasi-Toeplitz linear systems

5. Probabilistic Load Flow Evaluation With Hybrid Latin Hypercube Sampling and Cholesky Decomposition

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