Structured Learning Team Seminar (Talk by Dr. Velmurugan GANDHI)

This is an online seminar. Registration is required.

【Structured Learning Team】
【Date】2021/Nov/４(Thu) 1400pm-1500pm (JST)
【Speaker】 Dr. Velmurugan GANDHI

【Zoom】https://zoom.us/j/91082668811?pwd=QUdCT29VVWJIRVA2L0pxUjBQd3pEQT09

Title: Synchronization Analysis of Neural Networks with Time Delays
Abstract
Neural networks have attracted the attention of many researchers from various domains over the last few decades due to their superiority in handling data and learning algorithms. As a result, wide applications of neural systems are found in diverse regions, such as pattern classification, language processing, complex systems modeling, control, optimization, and prediction. In both biological and artificial neural networks, the presence of time delays is unavoidable, and it is always a source of network system instability, chaos, and oscillation. By incorporating time delays into simple neural networks, we may be able to capture a wide range of behaviors. In this oral presentation, we first look at some fundamental mathematical models of neural networks with time delays, and their synchronization and control issues are subsequently discussed. More specifically, the finite-time synchronization and projective synchronization problems for a class of fractional-order memristor-based neural networks (FMNNs) with time delays will be considered. Based on the Laplace transform, the generalized Gronwall’s inequality, Mittag-Leffler functions, stability theorem of linear fractional-order systems with multiple time delays, and linear feedback control technique, some new sufficient criteria will be employed to guarantee the synchronization of addressed FMNNs. Finally, some numerical simulations are provided to show the effectiveness of our proposed theoretical approach.