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

• المؤلفون الرئيسيون: Zhang, Zhijun, Song, Yating, Zheng, Lunan, Luo, Yamei
• مؤلفون آخرون: School of Electrical and Electronic Engineering
• التنسيق: مقال
• اللغة: English
• منشور في: 2023
• الموضوعات: Engineering::Computer science and engineering; Antidisturbance; Global Convergence
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/170578
• المؤسسة: 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...