A Review on Zeroing Neural Networks
Chengze Jiang, Jie Gui, Long Jin, Shuai Li
TL;DR
This paper surveys the development and applications of zeroing neural networks, highlighting their implementation, theoretical analysis, and practical use in time-varying optimization and control.
Contribution
It provides a comprehensive review of ZNNs, clarifying their relationships, derivations, and recent advances in the field.
Findings
Summarizes key implementation methods of ZNNs
Analyzes theoretical foundations of ZNNs
Highlights practical applications in control systems
Abstract
Zeroing neural networks (ZNNs) have demonstrated outstanding performance on time-varying optimization and control problems. Nonetheless, few studies are committed to illustrating the relationship among different ZNNs and the derivation of them. Therefore, reviewing the advances for a systematical understanding of this field is desirable. This paper provides a survey of ZNNs' progress regarding implementing methods, analysis theory, and practical applications.
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Taxonomy
TopicsNeural Networks and Applications · Machine Learning and ELM · Model Reduction and Neural Networks