A jump-gain integral recurrent neural network for solving noise-disturbed time-variant nonlinear inequality problems

• Main Authors: Zhang, Zhijun, Song, Yating, Zheng, Lunan, Luo, Yamei
• Other Authors: School of Electrical and Electronic Engineering
• Format: Article
• Language: English
• Published: 2023
• Subjects: Engineering::Computer science and engineering; Antidisturbance; Global Convergence
• Online Access: https://hdl.handle.net/10356/170578
• Institution: Nanyang Technological University

Nonlinear inequalities are widely used in science and engineering areas, attracting the attention of many researchers. In this article, a novel jump-gain integral recurrent (JGIR) neural network is proposed to solve noise-disturbed time-variant nonlinear inequality problems. To do so, an integral er...