Further synchronization in finite time analysis for time-varying delayed fractional order memristive competitive neural networks with leakage delay

被引:80
作者
Pratap, A. [1 ]
Raja, R. [2 ]
Cao, Jinde [3 ]
Rajchakit, G. [4 ]
Alsaadi, Fuad E. [5 ]
机构
[1] Alagappa Univ, Dept Math, Karaikkudi 630004, Tamil Nadu, India
[2] Alagappa Univ, Ramanujan Ctr Higher Math, Karaikkudi 630004, Tamil Nadu, India
[3] Southeast Univ, Sch Math, Nanjing 211189, Jiangsu, Peoples R China
[4] Maejo Univ, Fac Sci, Dept Math, Chiang Mai, Thailand
[5] King Abdulaziz Univ, Fac Engn, Dept Elect & Comp Engn, Jeddah 21589, Saudi Arabia
关键词
Synchronization in finite time; Competitive-type neural networks; Memristor; Fractional order; Time-varying delay; Leakage delay; STABILITY ANALYSIS; EXPONENTIAL STABILITY; LAG SYNCHRONIZATION; INCOMMENSURATE; BIFURCATION; CONTROLLERS; SYSTEMS; SCALES; MODEL;
D O I
10.1016/j.neucom.2018.08.016
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This article mainly concerns the synchronization in finite-time to the time-varying delay fractional order memristive competitive neural networks (TMFCNNs) with leakage delay. By means of Fillipov's theory, Gronwall-Bellman integral inequality, Holder's inequality, and the Caputo derivative properties, the novel algebraic sufficient conditions are proposed to guarantee the synchronization in finite time of addressing TMFCNNs with non-integer order: 0 < p < 1/2 and 1/2 <= p < 1 via finite-time output feedback controller. Up to now, there are no relevant results in fractional order competitive-type neural networks, and this article makes filling up for this gap. The obtained results are improved to some existing results on integerorder memristive competitive neural networks. Finally, two numerical examples with simulations are also designed to confirm the merits of the proposed theoretical results, while we estimate the upper bound of the settling time for the synchronization errors. (C) 2018 Elsevier B.V.All rights reserved.
引用
收藏
页码:110 / 126
页数:17
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