Zobrazeno 1 - 10
of 123
pro vyhledávání: '"Jigui Jian"'
Autor:
Tingting Zhang, Jigui Jian
Publikováno v:
Nonlinear Analysis, Vol 27 (2022)
This article focuses on the global exponential synchronization (GES) for second-order state-dependent switched quaternion-valued neural networks (SOSDSQVNNs) with neutral-type and mixed delays. By proposing some new Lyapunov–Krasovskii functionals
Externí odkaz:
https://doaj.org/article/52a3afea995c4645aba94f0a6a0b3566
Autor:
Liangliang Li, Jigui Jian
Publikováno v:
Entropy, Vol 17, Iss 1, Pp 39-51 (2014)
This paper is concerned with the problem of finite-time synchronization in complex networks with stochastic noise perturbations. By using a novel finite-time ℒ -operator differential inequality and other inequality techniques, some novel sufficient
Externí odkaz:
https://doaj.org/article/0ee8a2a0c2b2478a819e3aa90a6554ce
Autor:
Qiu Peng, Jigui Jian
Publikováno v:
Mathematics and Computers in Simulation. 205:62-77
Publikováno v:
Mathematics and Computers in Simulation. 202:223-245
Autor:
Xiulei Wang, Jigui Jian
Publikováno v:
Neural Processing Letters. 55:1759-1781
Publikováno v:
Neural Processing Letters. 54:1351-1369
Autor:
Jigui Jian, Kai Wu
Publikováno v:
IEEE Transactions on Neural Networks and Learning Systems. 32:5675-5687
This article focuses on the global robust exponential dissipativity (GRED) of uncertain second-order BAM neural networks with mixed time-varying delays. First, a new differential inequality for the concerned second-order system is established. Second
Publikováno v:
International Journal of Adaptive Control and Signal Processing. 36:88-103
Publikováno v:
IEEE Transactions on Fuzzy Systems. 29:3154-3164
This article focuses on the global Mittag-Leffler boundedness for fractional-order fuzzy quaternion-valued neural networks (QVNNs) with linear threshold neurons. In order to avert the nonexchangeability for quaternion multiplication, the considered Q
Autor:
Kai Wu, Jigui Jian
Publikováno v:
Neurocomputing. 436:174-183
The issue of the global dissipativity of memristive neutral-type inertial neural networks with distributed and discrete time-varying delays is discussed without converting the original system to first-order equations. By taking some new Lyapunov–Kr