Filters








591 Hits in 6.6 sec

Global Exponential Stability of Bidirectional Associative Memory Neural Networks With Time Delays

Xin-Ge Liu, R.R. Martin, Min Wu, Mei-Lan Tang
2008 IEEE Transactions on Neural Networks  
In this paper, we consider delayed bidirectional associative memory (BAM) neural networks (NNs) with Lipschitz continuous activation functions.  ...  Index Terms-Bidirectional associative memory (BAM) neural networks (NNs), global exponential stability, Lyapunov functionals, Young's inequality.  ...  Since Kosto [10] introduced bidirectional associative memory (BAM) NNs, researchers have paid particular attention to the stability analysis of BAM NNs with time delays, as such NNs have been shown to  ... 
doi:10.1109/tnn.2007.908633 pmid:18334360 fatcat:agxf6vrtwrc3rkqc4f66z53dbm

Delay-independent stability in bidirectional associative memory networks

K. Gopalsamy, Xue-Zhong He
1994 IEEE Transactions on Neural Networks  
associated with exogenous inputs to the network; both discrete and continuously distributed delays are considered; the asymptotic stability is global in the state space of neuronal activations and also  ...  It is shown that if the neuronal gains are small compared with the synaptic connection weights, then a bidirectional associative memory network with axonal signal transmission delays converges to the equilibria  ...  We shall now consider a class of bidirectional associative memory networks with continuously distributed delays described by For an extensive discussion of the stability and asymptotic behavior of integro-differential  ... 
doi:10.1109/72.329700 pmid:18267876 fatcat:5dcwxworkraghcrcb2ueurfpuu

Robust Stability Analysis of Neutral-Type Hybrid Bidirectional Associative Memory Neural Networks with Time-Varying Delays

Wei Feng, Simon X. Yang, Haixia Wu
2014 Abstract and Applied Analysis  
The global asymptotic robust stability of equilibrium is considered for neutral-type hybrid bidirectional associative memory neural networks with time-varying delays and parameters uncertainties.  ...  Therefore, the results of this paper are applicable to a larger class of neural networks and can be easily verified when compared with the previously reported literature results.  ...  Acknowledgments This work is supported by National Natural Science Foundation of China (no. 61103211) and Postdoctoral Science Foundation of Chongqing (no. XM201310).  ... 
doi:10.1155/2014/560861 fatcat:65lyxrxbx5b6nkdgowvzpocr5q

Global exponential stability and periodicity of recurrent neural networks with time delays

Jinde Cao, Jun Wang
2005 IEEE Transactions on Circuits and Systems I Fundamental Theory and Applications  
The delayed neural network includes the well-known Hopfield neural networks, cellular neural networks, and bidirectional associative memory networks as its special cases.  ...  In this paper, the global exponential stability and periodicity of a class of recurrent neural networks with time delays are addressed by using Lyapunov functional method and inequality techniques.  ...  Obviously, the neural network model includes the wellknown Hopfield neural networks, cellular neural networks, and bidirectional associative memory networks as its special cases.  ... 
doi:10.1109/tcsi.2005.846211 fatcat:fik5nmxbsfgldlabft5u3dpg4m

Robust Adaptive Control of Unknown Modified Cohen–Grossberg Neural Networks With Delays

Wenwu Yu, Jinde Cao, Guanrong Chen
2007 IEEE transactions on circuits and systems - 2, Analog and digital signal processing  
Index Terms-Global asymptotical stability, Lyapunov functional method, matrix inequality, modified Cohen-Grossberg neural network, nonsmooth analysis, time delay.  ...  In this brief, robust adaptive control of unknown modified Cohen-Grossberg neural networks with time delays is considered based on nonsmooth analysis and matrix inequality technique.  ...  Cao and Song [26] proposed a delayed Cohen-Grossberg type bidirectional associative memory network and studied its stability.  ... 
doi:10.1109/tcsii.2007.894427 fatcat:jmhukmvcu5hz3fsgw4so7tqrva

Exponential Stability Analysis of Neural Networks with Multiple Time Delays [chapter]

Huaguang Zhang, Zhanshan Wang, Derong Liu
2005 Lecture Notes in Computer Science  
Without assuming the boundedness, strict monotonicity and differentiability of the activation function, a result is established for the global exponential stability of a class of neural networks with multiple  ...  time delays.  ...  Acknowledgements This work was supported by the National Natural Science Foundation of China under Grants 60274017 and 60325311.  ... 
doi:10.1007/11427391_21 fatcat:qt2azqxg35abrj7u7kkp6gg2u4

Global Exponential Stability Criteria for Bidirectional Associative Memory Neural Networks with Time-Varying Delays

J. Thipcha, P. Niamsup
2013 Abstract and Applied Analysis  
The global exponential stability for bidirectional associative memory neural networks with time-varying delays is studied.  ...  By constructing new and improved Lyapunov-Krasovskii functional and introducing free-weighting matrices, a new and improved delay-dependent exponential stability for BAM neural networks with time-varying  ...  The second author is supported by the Centre of Excellence in Mathematics, Thailand and Commission for Higher Education, Thailand.  ... 
doi:10.1155/2013/576721 fatcat:367kpa3xzbexbldakbn2giqzji

New robust stability results for bidirectional associative memory neural networks with multiple time delays

Sibel Senan, Sabri Arik, Derong Liu
2012 Applied Mathematics and Computation  
associative memory (BAM) neural networks with multiple time delays.  ...  In this paper, we study the equilibrium and robust stability properties of hybrid bidirectional associative memory neural networks with multiple time delays.  ...  and the global robust asymptotic stability of the equilibrium point have been derived for a class of hybrid bidirectional associative memory (BAM) neural networks with multiple time delays.  ... 
doi:10.1016/j.amc.2012.04.075 fatcat:atc3af23p5f2daln4h7p5c56ea

A DELAY-DEPENDENT APPROACH TO ROBUST STABILITY FOR UNCERTAIN HYBRID BIDIRECTIONAL ASSOCIATIVE MEMORY NEURAL NETWORKS WITH TIME-VARYING DELAYS

Chien-Yu Lu, Koan-Yuh Chang, Hsun-Heng Tsai, Wen-Jer Chang
2010 Journal of Marine Science and Technology  
This paper performs a global robust stability analysis of a particular class of hybrid bidirectional associative memory time-varying delayed neural network with norm-bounded timevarying parameter uncertainties  ...  Globally delay-dependent robust stability criteria are derived in the form of linear matrix inequalities by introducing relaxation matrices which, when chosen properly, produce a less conservative result  ...  Accordingly, this paper addresses the problem of attaining globally robust stability in uncertain hybrid BAM neural networks with time-varying delays.  ... 
doi:10.51400/2709-6998.2315 fatcat:lqikemk2ojfxbi56hqbj3sxkyy

Stability Criterion for BAM Neural Networks of Neutral-Type with Interval Time-Varying Delays

Guoquan Liu, Simon X. Yang
2011 Procedia Engineering  
In this paper, the asymptotic stability for bidirectional associative memory (BAM) neural networks of neutral-type with interval time-varying delays is investigated.  ...  The discrete delay is assumed to be time-varying and belong to a given interval, which means that the lower and upper bounds of interval time-varying delays are available.  ...  Introduction It is well known that bidirectional associative memory (BAM) neural network is a type of recurrent neural network. BAM neural network was introduced by [1]- [2] .  ... 
doi:10.1016/j.proeng.2011.08.534 fatcat:ns6joy7pkngw7eacc5ekpw3eiq

Stability analysis of discrete-time BAM neural networks based on standard neural network models

Zhang Sen-lin, Liu Mei-qin
2005 Journal of Zhejiang University: Science A  
We propose a new approach for analyzing the global asymptotic stability of the extended discrete-time bidirectional associative memory (BAM) neural networks.  ...  Keywords: standard neural network nKxiel, bidirectional associative memory, discrete-time, linear matrix inequality, global asymptotic stability.  ...  Bidirectional associative memory model is a kind of neural network models in common use with the ability of information memory and association.  ... 
doi:10.1631/jzus.2005.a0689 fatcat:ah636pbnz5felimaghkhxyahyi

Global asymptotic stability of a general class of recurrent neural networks with time-varying delays

Jinde Cao, Jun Wang
2003 IEEE Transactions on Circuits and Systems I Fundamental Theory and Applications  
In this paper, the existence and uniqueness of the equilibrium point and its global asymptotic stability are discussed for a general class of recurrent neural networks with time-varying delays and Lipschitz  ...  The neural network model considered includes the delayed Hopfield neural networks, bidirectional associative memory networks, and delayed cellular neural networks as its special cases.  ...  GLOBAL ASYMPTOTIC STABILITY In this section, we will give several sufficient conditions on the global asymptotic stability of equilibrium point for the recurrent neural network (1) with time-varying delays  ... 
doi:10.1109/tcsi.2002.807494 fatcat:bbeezdgvgfb6ph6eob3zikv23i

Global Stability, Bifurcation, and Chaos Control in a Delayed Neural Network Model

Amitava Kundu, Pritha Das
2014 Advances in Artificial Neural Systems  
Conditions for the global asymptotic stability of delayed artificial neural network model of n (≥3) neurons have been derived.  ...  For bifurcation analysis with respect to delay we have considered the model with three neurons and used suitable transformation on multiple time delays to reduce it to a system with single delay.  ...  Conflict of Interests The authors declare that there is no conflict of interests regarding the publication of this paper.  ... 
doi:10.1155/2014/369230 fatcat:2hidmseyljg45efxhucksvqqcm

Novel stability criteria for bidirectional associative memory neural networks with time delays

Xiaofeng Liao, Juebang Yu, Guanrong Chen
2002 International journal of circuit theory and applications  
In this paper, the bidirectional associative memory (BAM) neural network with axonal signal transmission delay is considered. This model is also referred to as a delayed dynamic BAM model.  ...  By combining a number of di erent Lyapunov functionals with the Razumikhin technique, some su cient conditions for the existence of a unique equilibrium and global asymptotic stability of the network are  ...  This work was supported by the Hong Kong Research Grants Council under the Grant 9040565, and by the Applying Basic Research Grants Committee of Science and Technology of Chongqing.  ... 
doi:10.1002/cta.206 fatcat:g7at5veasfcsbfsmaalizrif6e

Almost Periodic Solution for Memristive Neural Networks with Time-Varying Delays

Huaiqin Wu, Luying Zhang
2013 Journal of Applied Mathematics  
This paper is concerned with the dynamical stability analysis for almost periodic solution of memristive neural networks with time-varying delays.  ...  Moreover, as a special case, the condition which ensures the global exponential stability of a unique periodic solution is also presented for the considered memristive neural networks.  ...  Journal of Applied Mathematics  ... 
doi:10.1155/2013/716172 fatcat:ezcp6ipsszfu7c44iiej5zz5gq
« Previous Showing results 1 — 15 out of 591 results