Complex Dynamical Network Control for Trajectory Tracking Using Delayed Recurrent Neural Networks
Joint Authors
Flores Hemandez, Angel
Arroyo, Santiago
Perez, Jose P.
Perez Padron, Joel
Source
Mathematical Problems in Engineering
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-01-02
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
In this paper, the problem of trajectory tracking is studied.
Based on the V-stability and Lyapunov theory, a control law that achieves the global asymptotic stability of the tracking error between a delayed recurrent neural network and a complex dynamical network is obtained.
To illustrate the analytic results, we present a tracking simulation of a dynamical network with each node being just one Lorenz’s dynamical system and three identical Chen’s dynamical systems.
American Psychological Association (APA)
Perez, Jose P.& Perez Padron, Joel& Flores Hemandez, Angel& Arroyo, Santiago. 2014. Complex Dynamical Network Control for Trajectory Tracking Using Delayed Recurrent Neural Networks. Mathematical Problems in Engineering،Vol. 2014, no. 2014, pp.1-7.
https://search.emarefa.net/detail/BIM-450843
Modern Language Association (MLA)
Perez, Jose P.…[et al.]. Complex Dynamical Network Control for Trajectory Tracking Using Delayed Recurrent Neural Networks. Mathematical Problems in Engineering No. 2014 (2014), pp.1-7.
https://search.emarefa.net/detail/BIM-450843
American Medical Association (AMA)
Perez, Jose P.& Perez Padron, Joel& Flores Hemandez, Angel& Arroyo, Santiago. Complex Dynamical Network Control for Trajectory Tracking Using Delayed Recurrent Neural Networks. Mathematical Problems in Engineering. 2014. Vol. 2014, no. 2014, pp.1-7.
https://search.emarefa.net/detail/BIM-450843
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-450843