Robust dissipativity analysis of hopfield-type complex-valued neural networks with time-varying delays and linear fractional uncertainties

• Main Authors: Pharunyou Chanthorn, Grienggrai Rajchakit, Sriraman Ramalingam, Chee Peng Lim, Raja Ramachandran
• Format: Journal
• Published: 2020
• Subjects: Mathematics
• Online Access: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85084480207&origin=inward; http://cmuir.cmu.ac.th/jspui/handle/6653943832/70721
• Institution: Chiang Mai University

© 2020 by the authors. We study the robust dissipativity issue with respect to the Hopfield-type of complex-valued neural network (HTCVNN) models incorporated with time-varying delays and linear fractional uncertainties. To avoid the computational issues in the complex domain, we divide the original complex-valued system into two real-valued systems. We devise an appropriate Lyapunov-Krasovskii functional (LKF) equipped with general integral terms to facilitate the analysis. By exploiting the multiple integral inequality method, the sufficient conditions for the dissipativity of HTCVNN models are obtained via the linear matrix inequalities (LMIs). The MATLAB software package is used to solve the LMIs effectively. We devise a number of numerical models and their empirical results positively ascertain the obtained results.