Results 301 to 310 of about 1,813,184 (347)

Saturated impulsive control for synchronization of coupled delayed neural networks

Neural Networks, 2021
Shuchen Wu, Xiaodi Li, Yanhui Ding
semanticscholar   +1 more source

Finite-time synchronization of time-delayed neural networks with unknown parameters via adaptive control

Neurocomputing, 2018
In this paper, the problem of finite-time adaptive synchronization is investigated for two different delayed neural networks with unknown parameters. Two adaptive control approaches are designed in order to synchronize the neural networks in finite time.
Shanqiang Li, Xiuyan Peng, Yu Tang, Yujing Shi   +3 more
semanticscholar   +1 more source

Stability of delayed cellular neural networks

Chaos, Solitons & Fractals, 2007
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Zhang, Qiang, Wei, Xiaopeng, Xu, Jin
openaire   +1 more source

System Identification with Delayed Neural Network

2008 Fourth International Conference on Natural Computation, 2008
In this brief, the identification problem for time-varying delay nonlinear system is discussed. We use a delayed dynamic neural network to do on-line identification. This neural network has dynamic series-parallel structure. The stability conditions of on-line identification are derived by Lyapunov-Krasovskii approach. The weights of the delayed neural
Pu Wang, Xueli Wu, Bin Wang, Jianhua Zhang   +3 more
openaire   +1 more source

Stability of stochastic delay neural networks

Journal of the Franklin Institute, 2001
The stochastically perturbed network with delays \[ dx(t)= \bigl[ -Bx(t)+ Ag\bigl(x_\tau (t)\bigr) \biggr]dt +\sigma\bigl( x(t),x_\tau (t), t\bigr)dw(t), t\geq 0;\;x(s)=\xi(s),\;-\tau\leq s\leq 0;\tag{1} \] is considered. Here \(w(t)\) is an \(m\)-dimensional Brownian motion, \(\sigma(x,y,t)\) is locally Lipschitz continuous and satisfies the linear ...
Blythe, Steve, Mao, Xuerong, Liao, Xiaoxin   +2 more
openaire   +2 more sources

Global stability of neural networks with distributed delays

Physical Review E, 2003
In this paper, a model describing the dynamics of recurrent neural networks with distributed delays is considered. Some sufficient criteria are derived ensuring the global asymptotic stability of distributed-delay recurrent neural networks with more general signal propagation functions by introducing real parameters p>1, q(ij)>0, and r(jj)>0, i,j=1, em
openaire   +4 more sources

Deep delay rectified neural networks

The Journal of Supercomputing, 2022
Chuanhui Shan, Ao Li, Xiumei Chen
openaire   +1 more source

Chaotic Synchronization of Delayed Neural Networks

2005
In this paper, synchronization issue of a coupled time-delayed neural system with chaos is investigated. A sufficient condition for determining the exponential synchronization between the drive and response systems is derived via Lyapunov-Krasovskii stability theorem.
Fenghua Tu, Xiaofeng Liao, Chuandong Li
openaire   +1 more source

Binary Neural Network with Delayed Synapses

1991
Although the neuron with sigmoidal function is usually used to construct the neural network, it is difficult to be fabricated within the chip. The neural network with only binary neurons (in short, the binary neural network) is less powerful than the general neural network (Bruck and Goodman 1987).
Tadashi Ae, Yasuhiro Mitsui, Satoshi Fujita, Reiji Aibara   +3 more
openaire   +1 more source

Stochastic Stabilization of Delayed Neural Networks

2007
By introducing appropriate stochastic factors into the neural networks, there were results showing that the neural networks can be stabilized. In this paper, stochastic stabilization of delayed neural networks is studied. First, a new type Razumikhin-type theorem about stochastic functional differential equations is proposed and the rigid proof is ...
Wudai Liao, Jinhuan Chen, Yulin Xu, Xiaoxin Liao   +3 more
openaire   +1 more source