23 Hits in 18.6 sec

Mean-Square Exponential Input-to-State Stability of Stochastic Fuzzy Recurrent Neural Networks with Multiproportional Delays and Distributed Delays

Tianyu Wang, Quanxin Zhu, Jingwei Cai
2018 Mathematical Problems in Engineering  
We are interested in a class of stochastic fuzzy recurrent neural networks with multiproportional delays and distributed delays.  ...  input-to-state stability of the suggested system.  ...  Acknowledgments This work was jointly supported by the National Natural Science Foundation of China (61773217 and 61374080), the Natural Science Foundation of Jiangsu Province (BK20161552), and Qing Lan  ... 
doi:10.1155/2018/6289019 fatcat:nr6cy4mar5hhdfvszuvjwqi7si

Mean almost periodicity and moment exponential stability of semi-discrete random cellular neural networks with fuzzy operations

Sufang Han, Guoxin Liu, Tianwei Zhang, Jun Ma
2019 PLoS ONE  
By using the semi-discretization technique of differential equations, the discrete analogue of a kind of cellular neural networks with stochastic perturbations and fuzzy operations is formulated, which  ...  Finally, a problem of stochastic stabilization for discrete cellular neural networks is studied.  ...  Acknowledgments The authors would like to extend their thanks to the referees for their careful reading of the manuscript and insightful comments.  ... 
doi:10.1371/journal.pone.0220861 pmid:31390372 pmcid:PMC6685627 fatcat:6zodok445vezffglpoene4jna4

Mean-square exponential stability of fuzzy stochastic BAM networks with hybrid delays

Fosheng Wang, Chengqiang Wang
2018 Advances in Difference Equations  
We study fuzzy stochastic bidirectional associative memory cellular neural networks with discrete delays in leakage terms and with continuous and infinitely distributed delays in the transmission terms  ...  Under certain structural assumptions, we prove that the networks in question are mean-square exponentially stable.  ...  Acknowledgements Fosheng is supported by the Initial Foundation of Mianyang Teachers' College (Grant No. QD2016A003).  ... 
doi:10.1186/s13662-018-1690-z fatcat:t3ce6qb3wvgqzg6smscopr2d2a

Stochastic Synchronization of Reaction-Diffusion Neural Networks under General Impulsive Controller with Mixed Delays

Xinsong Yang, Chuangxia Huang, Zhichun Yang
2012 Abstract and Applied Analysis  
This paper investigates drive-response synchronization of a class of reaction-diffusion neural networks with time-varying discrete and distributed delays via general impulsive control method.  ...  Based on a novel impulsive differential inequality, the properties of random variables and Lyapunov functional method, sufficient conditions guaranteeing the global exponential synchronization in mean  ...  The authors of 25 studied exponential stability of reaction-diffusion Cohen-Grossberg neural networks with time-varying discrete delays and stochastic perturbations.  ... 
doi:10.1155/2012/603535 fatcat:tjsorvjvdrbofgsjksefth56r4

2021 Index IEEE Transactions on Cybernetics Vol. 51

2021 IEEE Transactions on Cybernetics  
Note that the item title is found only under the primary entry in the Author Index.  ...  The primary entry includes the coauthors' names, the title of the paper or other item, and its location, specified by the publication abbreviation, year, month, and inclusive pagination.  ...  ., +, TCYB May 2021 2457-2465 Multiple Mittag-Leffler Stability of Delayed Fractional-Order Cohen-Grossberg Neural Networks via Mixed Monotone Operator Pair.  ... 
doi:10.1109/tcyb.2021.3139447 fatcat:myjx3olwvfcfpgnwvbuujwzyoi

Stability of stochastic neural networks of neutral type with Markovian jumping parameters: A delay-fractioning approach

R. Rakkiyappan, Quanxin Zhu, A. Chandrasekar
2014 Journal of the Franklin Institute  
This paper deals with the stochastically asymptotic stability in the mean square for a new class of stochastic neural networks of neutral type with both Markovian jump parameters and mixed time delays.  ...  jumping stochastic Cohen-Grossberg neural networks with discrete interval and distributed delays; Very recently, Zhu and Cao studied the exponential stability for several new classes of Markovian jump  ...  Moreover, we have investigated stochastically asymptotic stability in the mean square of Markovian jump stochastic neutral type neural networks and the result has been derived by constructing a new Lyapunov-Krasovskii  ... 
doi:10.1016/j.jfranklin.2013.11.017 fatcat:k4cmwqisdnfz3fwx2wwnqggnue

A Taxonomy for Spatiotemporal Connectionist Networks Revisited: The Unsupervised Case

Guilherme de A. Barreto, Aluizio F. R. Araújo, Stefan C. Kremer
2003 Neural Computation  
Spatiotemporal connectionist networks (STCNs) comprise an important class of neural models that can deal with patterns distributed in both time and space.  ...  In this article, we widen the application domain of the taxonomy for supervised STCNs recently proposed by Kremer (2001) to the unsupervised case.  ...  We also thank the reviewers for their insightful suggestions to improve the article.  ... 
doi:10.1162/089976603321780281 pmid:12816574 fatcat:duvonguvxrbnxbicygfuypumhm

2021 Index IEEE Transactions on Systems, Man, and Cybernetics: Systems Vol. 51

2021 IEEE Transactions on Systems, Man & Cybernetics. Systems  
Note that the item title is found only under the primary entry in the Author Index.  ...  The primary entry includes the coauthors' names, the title of the paper or other item, and its location, specified by the publication abbreviation, year, month, and inclusive pagination.  ...  ., TSMC July 2021 4227-4237 Multiple ψ-Type Stability of Cohen-Grossberg Neural Networks With Unbounded Time-Varying Delays.  ... 
doi:10.1109/tsmc.2021.3136054 fatcat:b5hcsfwjw5hllpenqmaq6wpke4

A Delay-Dividing Approach to Robust Stability of Uncertain Stochastic Complex-Valued Hopfield Delayed Neural Networks

Pharunyou Chanthorn, Grienggrai Rajchakit, Usa Humphries, Pramet Kaewmesri, Ramalingam Sriraman, Chee Peng Lim
2020 Symmetry  
In the present study, a delay-dividing approach is devised to study the robust stability issue of uncertain neural networks.  ...  Specifically, the uncertain stochastic complex-valued Hopfield neural network (USCVHNN) with time delay is investigated. Here, the uncertainties of the system parameters are norm-bounded.  ...  Acknowledgments: The authors are grateful to the support provided by Chiang Mai University. Conflicts of Interest: The authors declare no conflict of interest. Symmetry 2020, 12, 683  ... 
doi:10.3390/sym12050683 fatcat:iax6p2zzkbawdbjis2duny5f7m

2020 Index IEEE Transactions on Neural Networks and Learning Systems Vol. 31

2020 IEEE Transactions on Neural Networks and Learning Systems  
Note that the item title is found only under the primary entry in the Author Index.  ...  The primary entry includes the coauthors' names, the title of the paper or other item, and its location, specified by the publication abbreviation, year, month, and inclusive pagination.  ...  ., +, TNNLS Jan. 2020 331-344 Multistability of Almost Periodic Solution for Memristive Cohen-Grossberg Neural Networks With Mixed Delays.  ... 
doi:10.1109/tnnls.2020.3045307 fatcat:34qoykdtarewhdscxqj5jvovqy

Robustness Analysis of Exponential Stability of Neutral-type Nonlinear Systems with Multi-interference

Wen-Xiao Si, Tao Xie, Bi-Wen Li
2021 IEEE Access  
With a view to the unfavorable impact of the inevitable exogenous interferences for the practical engineering and signal transmission, here we focus on the robustness of global exponential stability for  ...  Through the strategies mentioned above, a class of algebraic problems of estimating three upper bounds by solving transcendental equations with three variables is settled.  ...  [33] studied the interval fuzzy robust exponential stability of Cohen-Grossberg networks by means of the comparison principle. Ref.  ... 
doi:10.1109/access.2021.3105521 fatcat:q3g5w7427baxlpdwyjuf25suwu

Recurrent Neural Networks: Associative Memory and Optimization

K. -L. Du
2011 Journal of Information Technology & Software Engineering  
A learning problem in a Hopfield network with J units can be transformed into a learning problem for a perceptron of dimension ( 1) 2 J J + [99], and thus every learning  ...  Due to feedback connections, recurrent neural networks (RNNs) are dynamic models.  ...  Equation (9) is a special case of the Cohen-Grossberg model [24] . An inspection of (6) and (3) shows that α is zero in the basic Hopfield model.  ... 
doi:10.4172/2165-7866.1000104 fatcat:zqfpc2fpwzhufigwozssmylotu

Financial volatility trading using a self-organising neural-fuzzy semantic network and option straddle-based approach

W.L. Tung, C. Quek
2011 Expert systems with applications  
The VPM is realized by a self-organising neural-fuzzy semantic network named the evolving fuzzy semantic memory (eFSM) model.  ...  Financial volatility refers to the intensity of the fluctuations in the expected return on an investment or the pricing of a financial asset due to market uncertainties.  ...  is known as the stability-plasticity dilemma (Grossberg, 1982) .  ... 
doi:10.1016/j.eswa.2010.07.116 pmid:32288336 pmcid:PMC7126939 fatcat:lnjtwuli3bh5nbqvvxzleu4oki

Recurrent Neural Networks [chapter]

Sajid A. Marhon, Christopher J. F. Cameron, Stefan C. Kremer
2013 Intelligent Systems Reference Library  
Some authors discuss aspects of improving recurrent neural network performance and connections with Bayesian analysis and knowledge representation, including extended neuro-fuzzy systems.  ...  Problems dealing with trajectories, control systems, robotics, and language learning are included, along with an interesting use of recurrent neural networks in chaotic systems.  ...  Lund and Stefano Nolfi who did most of the development of the kepsim simulator, which has been used (in slightly adapted form) to implement the experiments documented in this paper.  ... 
doi:10.1007/978-3-642-36657-4_2 fatcat:jnmgv7rlifhuncqhi5kxldepdm

Artificial neural networks

J.J. Hopfield
1988 IEEE Circuits & Devices  
The mean-square error criterion is defined as: , (2.124) where E(.) is the expectation operator, and e=t-y is the error vector.  ...  Class. 3 70 0.832 4 17 0.838 τ 10 6 - = Table 3 .1 -Parameters 3 Mean Covariance Matrices Table 4 . 1 - 41 Correspondence between Cohen-Grossberg and Hopfield modelsCohen-Grossberg  ...  If we can find a Lyapunov function for the particular system at hand we prove global stability of the system.  ... 
doi:10.1109/101.8118 fatcat:c6royelcdzfethnmmur2tj524i
« Previous Showing results 1 — 15 out of 23 results