Extended analysis on the global Mittag-Leffler synchronization problem for fractional-order octonion-valued BAM neural networks.

Journal: Neural networks : the official journal of the International Neural Network Society
Published Date:

Abstract

In this paper, a new case of neural networks called fractional-order octonion-valued bidirectional associative memory neural networks (FOOVBAMNNs) is established. First, the higher dimensional models are formulated for FOOVBAMNNs with general activation functions and the special linear threshold ones, respectively. On one hand, employing Cayley-Dichson construction in octonion multiplication which is essentially neither commutative nor associative, the system of FOOVBAMNNs is divided into four fractional-order complex-valued ones. On the other hand, Caputo fractional derivative's character and BAM's interactive feature are also properly dealt with. Second, the general criteria are obtained by the new design of LKFs, the application of the related inequalities and the construction of the linear feedback controllers for the global Mittag-Leffler synchronization problem of FOOVBAMNNs. Finally, we present two numerical examples to show the realizability and progress of the derived results.

Authors

  • Jianying Xiao
    School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu 611731, PR China; School of Sciences, Southwest Petroleum University, Chengdu 610050, PR China. Electronic address: shawion1980@yahoo.com.
  • Xiao Guo
    School of Pharmacy, Beihua University, Jilin, China.
  • Yongtao Li
    College of Chemistry and Chemical Engineering, Southwest Petroleum University, Chengdu 610050, PR China.
  • Shiping Wen
  • Kaibo Shi
    School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, PR China. Electronic address: skbs111@163.com.
  • YiQian Tang
    College of Computer, Chengdu University, Chengdu, China.