Published August 2018 | Version v1
Journal article

Finite-time anti-synchronization of memristive stochastic BAM neural networks with probabilistic time-varying delays

  • 1. Beijing Key Laboratory of Knowledge Engineering for Materials Science, Beijing 100083 (China)
  • 2. School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing 100083 (China)
  • 3. Institute of Physics, Humboldt-University, Berlin 10099 (Germany)
  • 4. Institute of Microstructure and Properties of Advanced Materials, Beijing University of Technology, Beijing 100124 (China)
  • 5. Department of Electrical Engineering and Computer Science, Cleveland State University, Cleveland, OH 44115 (United States)

Description

This paper investigates the drive-response finite-time anti-synchronization for memristive bidirectional associative memory neural networks (MBAMNNs). Firstly, a class of MBAMNNs with mixed probabilistic time-varying delays and stochastic perturbations is first formulated and analyzed in this paper. Secondly, an nonlinear control law is constructed and utilized to guarantee drive-response finite-time anti-synchronization of the neural networks. Thirdly, by employing some inequality technique and constructing an appropriate Lyapunov function, some anti-synchronization criteria are derived. Finally, a number simulation is provided to demonstrate the effectiveness of the proposed mechanism.

Availability note (English)

Available from http://dx.doi.org/10.1016/j.chaos.2018.06.013

Additional details

Identifiers

DOI
10.1016/j.chaos.2018.06.013;
PII
S0960077918303941;

Publishing Information

Journal Title
Chaos, Solitons and Fractals
Journal Volume
113
Journal Page Range
p. 244-260
ISSN
0960-0779

INIS

Country of Publication
United Kingdom
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
51023534
Subject category
S97: MATHEMATICAL METHODS AND COMPUTING;
Descriptors DEI
FUNCTIONS; LYAPUNOV METHOD; NEURAL NETWORKS; PERTURBATION THEORY; PROBABILISTIC ESTIMATION; SIMULATION; STOCHASTIC PROCESSES; SYNCHRONIZATION
Descriptors DEC
CALCULATION METHODS

Optional Information

Notes
© 2018 Elsevier Ltd. All rights reserved.