On global asymptotic stability of neural networks with discrete and distributed delays

By Zidong Wang, Yurong Liu, Xiaohui Liu. 2005

426 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/c098cbaf6e527fff6d3a39d35ebbd50eb965d50a

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In Computer Networks and Communications

In Electrical and Electronic Engineering

Citations in the corpus

New Delay-Dependent Exponential $H_{\infty}$ Synchronization for Uncertain Neural Networks With Mixed Time Delays (2010, background): “It is noted that both discrete and distributed time delays have recently been considered in [27], [28], [33], and [ 38 ].”
Exponential stability of delayed recurrent neural networks with Markovian jumping parameters (2006, methodology): “[4], [9], [12], [15] for some recent publications, where many methods have been exploited, such as the LMI approach and M -matrix approach.”
Stability and Synchronization of Discrete-Time Markovian Jumping Neural Networks With Mixed Mode-Dependent Time Delays (2009, background): “Various sufficient conditions, either delay-dependent or delay-independent , have been proposed to guarantee the global asymptotic or exponential stability for the RNNs; see, e.g., [6], [34], [38], [39], and [41] for some recent publications.”
Global Synchronization in an Array of Delayed Neural Networks With Hybrid Coupling (2008, background): “Most of the previous studies mainly concentrated on stability analysis, periodic or almost periodic attractors, and dissipativity of recurrent neural networks with or without delays (see [1]–[6], and [33] and the references cited therein; some new results about stochastic NNs have been reported in [”
New Delay-Dependent Stability Criteria for Neural Networks With Time-Varying Delay (2007, background): “[ 13 ] M. J. L. Orr, “Regularization in the selection of radial basis function”
Global Asymptotical Stability of Recurrent Neural Networks With Multiple Discrete Delays and Distributed Delays (2006, background): “Since a neural network usually has a spatial nature due to the presence of an amount of parallel pathways of a variety of axon sizes and lengths, it is desired to model them by introducing continuously distributed delays over a certain duration of time, such that the distant past has less influence ”
A Comprehensive Review of Stability Analysis of Continuous-Time Recurrent Neural Networks (2014, methodology): “2) The following activation functions have been used in [137], [265], [272], [301], and [315]: |g i (ζ ) − g i (ξ )| ≤ δ i |ζ − ξ | (17) no matter whether the activation function is bounded or not.”