Weak and strong convergence analysis of Elman neural networks via weight decay regularization-Reference-Cited by-同舟云学术

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Weak and strong convergence analysis of Elman neural networks via weight decay regularization

Published:2022-04-04 Issue: Volume: Page:1-23
ISSN:0233-1934
Container-title:Optimization
language:en
Short-container-title:Optimization

Author:

Zhou Li¹,Fan Qinwei¹,Huang Xiaodi²,Liu Yan³

Affiliation:

1. School of Science, Xi'an Polytechnic University, Xi'an, People's Republic of China

2. School of Computing, Mathematics and Engineering, Charles Sturt University, Albury, NSW, Australia

3. School of Information Science and Engineering, Dalian Polytechnic University, Dalian, People's Republic of China

Funder

Natural Science Basic Research Plan in Shaanxi Province of China

China Postdoctoral Science Foundation

Natural Science Foundation Guidance Project of Liaoning Province

Publisher

Informa UK Limited

Subject

Applied Mathematics,Management Science and Operations Research,Control and Optimization

Link

https://www.tandfonline.com/doi/pdf/10.1080/02331934.2022.2057852

Reference54 articles.

1. Learning representations by back-propagating errors

2. Robust feature selection via nonconvex sparsity-based methods

3. Robust Exponential Stability of Uncertain Delayed Neural Networks With Stochastic Perturbation and Impulse Effects

4. A short-term power load forecasting model based on the generalized regression neural network with decreasing step fruit fly optimization algorithm

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