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Hidden hyperchaotic attractor in a novel simple memristive neural network

VIET-THANH PHAM1,* , C. VOLOS2, S. JAFARI3, XIONG WANG4, SUNDARAPANDIAN VAIDYANATHAN5

Affiliation

  1. School of Electronics and Telecommunications, Hanoi University of Science and Technology, 01 Dai Co Viet, Hanoi, Vietnam
  2. Physics Department, Aristotle University of Thessaloniki, GR-54124, Greece
  3. Biomedical Engineering Department, Amirkabir University of Technology, Tehran 15875-4413, Iran
  4. Institute for Advanced Study, Shenzhen University, Shenzhen, Guangdong 518060, P.R. China
  5. Research and Development Centre, Vel Tech University, Avadi, Chennai-600062, Tamil Nadu, India

Abstract

Potential applications of memristors in low-power processors, ultra-dense memories, programmable analog integrated circuits, and especially neural networks, have been reported recently. This paper introduces a novel simple neural network having a memristive synaptic weight. Fundamental behavior of the proposed neural network is investigated through numerical simulations and circuital implementation. It is very interesting that this memristive neural network can exhibit hyperchaos although it possesses no equilibrium points..

Keywords

Neural network, Memristor, Hyperchaos, Hidden attractor, Equilibrium, Synapse, Lyapunov exponent.

Citation

VIET-THANH PHAM, C. VOLOS, S. JAFARI, XIONG WANG, SUNDARAPANDIAN VAIDYANATHAN, Hidden hyperchaotic attractor in a novel simple memristive neural network, Optoelectronics and Advanced Materials - Rapid Communications, 8, 11-12, November-December 2014, pp.1157-1163 (2014).

Submitted at: Aug. 28, 2014

Accepted at: Nov. 13, 2014