E
Edgar N. Sanchez
Researcher at CINVESTAV
Publications - 366
Citations - 4444
Edgar N. Sanchez is an academic researcher from CINVESTAV. The author has contributed to research in topics: Artificial neural network & Control theory. The author has an hindex of 28, co-authored 366 publications receiving 3987 citations. Previous affiliations of Edgar N. Sanchez include University of Guadalajara.
Papers
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Journal ArticleDOI
Delay-dependent exponential stability analysis of delayed neural networks: an LMI approach
TL;DR: The results obtained in this paper provide one more set of easily verified guidelines for determining the exponentially stability of delayed neural networks, which are less conservative and less restrictive than the ones reported so far in the literature.
Journal ArticleDOI
LMI-based approach for asymptotically stability analysis of delayed neural networks
TL;DR: In this paper, the authors derived sufficient conditions for asymptotic stability of neural networks with constant or time-varying delays, based on the Lyapunov-Krasovskii stability theory for functional differential equations and the linear matrix inequality approach.
Book
Differential Neural Networks for Robust Nonlinear Control: Identification, State Estimation and Trajectory Tracking
TL;DR: Theoretical Study: Neural Networks Structures Nonlinear System Identification: Differential Learning Sliding Mode Identification: Algebraic Learning Neural State Estimation Passivation via Neuro Control and Applications.
Proceedings ArticleDOI
Predefined-time stability of dynamical systems with sliding modes
TL;DR: This paper introduces a class of fixed-time stable dynamical systems with settling time as a explicit parameter, namely the inverse the gain, defined as predefined-timed stable Dynamical systems.
Book
Discrete-Time High Order Neural Control: Trained with Kalman Filtering
TL;DR: The objective of this work is to present recent advances in the theory of neural control for discrete-time nonlinear systems with multiple inputs and multiple outputs with rigorous mathematical analyses, based on the Lyapunov approach, that guarantee its properties.