Thematische Bibliographien / Delay -dependant dissipativity criteria

Auswahl der wissenschaftlichen Literatur zum Thema „Delay -dependant dissipativity criteria“

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Veröffentlicht am 17. Juli 2024

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Zeitschriftenartikel zum Thema "Delay -dependant dissipativity criteria"

1

Song, Qiankun, und Jinde Cao. „Global Dissipativity on Uncertain Discrete-Time Neural Networks with Time-Varying Delays“. Discrete Dynamics in Nature and Society 2010 (2010): 1–19. http://dx.doi.org/10.1155/2010/810408.

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The problems on global dissipativity and global exponential dissipativity are investigated for uncertain discrete-time neural networks with time-varying delays and general activation functions. By constructing appropriate Lyapunov-Krasovskii functionals and employing linear matrix inequality technique, several new delay-dependent criteria for checking the global dissipativity and global exponential dissipativity of the addressed neural networks are established in linear matrix inequality (LMI), which can be checked numerically using the effective LMI toolbox in MATLAB. Illustrated examples are given to show the effectiveness of the proposed criteria. It is noteworthy that because neither model transformation nor free-weighting matrices are employed to deal with cross terms in the derivation of the dissipativity criteria, the obtained results are less conservative and more computationally efficient.
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2

Hammachukiattikul, Porpattama. „Finite-time Stability, Dissipativity and Passivity Analysis of Discrete-time Neural Networks Time-varying Delays“. Emerging Science Journal 3, Nr. 6 (01.12.2019): 361–68. http://dx.doi.org/10.28991/esj-2019-01198.

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The neural network time-varying delay was described as the dynamic properties of a neural cell, including neural functional and neural delay differential equations. The differential expression explains the derivative term of current and past state. The objective of this paper obtained the neural network time-varying delay. A delay-dependent condition is provided to ensure the considered discrete-time neural networks with time-varying delays to be finite-time stability, dissipativity, and passivity. This paper using a new Lyapunov-Krasovskii functional as well as the free-weighting matrix approach and a linear matrix inequality analysis (LMI) technique constructing to a novel sufficient criterion on finite-time stability, dissipativity, and passivity of the discrete-time neural networks with time-varying delays for improving. We propose sufficient conditions for discrete-time neural networks with time-varying delays. An effective LMI approach derives by base the appropriate type of Lyapunov functional. Finally, we present the effectiveness of novel criteria of finite-time stability, dissipativity, and passivity condition of discrete-time neural networks with time-varying delays in the form of linear matrix inequality (LMI).
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3

Chen, Guici, Jianzhong Zhou und Yongchuan Zhang. „Dissipative Delay-Feedback Control for Nonlinear Stochastic Systems with Time-Varying Delay“. Mathematical Problems in Engineering 2014 (2014): 1–11. http://dx.doi.org/10.1155/2014/249860.

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The dissipative delay-feedback control problems for nonlinear stochastic delay systems (NSDSs) based on dissipativity analysis are studied in this paper. Based on the Lyapunov stability theory and stochastic analysis technique, both delay-independent and delay-dependent dissipativity criteria are established as linear matrix inequalities- (LMIs-) based feasibility tests. The obtained results in this paper for the nominal systems include the available results onH∞approach and passivity for stochastic delay systems as special cases. The delay-dependent feedback controller is designed by considering the relationship among the time-varying delay, its lower and upper bound, and its differential without ignoring any terms, which effectively reduces the conservative. A numerical example is given to illustrate the theoretical developments.
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4

Nagamani, G., Young Hoon Joo und T. Radhika. „Delay-dependent dissipativity criteria for Markovian jump neural networks with random delays and incomplete transition probabilities“. Nonlinear Dynamics 91, Nr. 4 (31.01.2018): 2503–22. http://dx.doi.org/10.1007/s11071-017-4028-6.

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5

Zhao, Zirui, und Wenjuan Lin. „Extended dissipative analysis for memristive neural networks with two-delay components via a generalized delay-product-type Lyapunov-Krasovskii functional“. AIMS Mathematics 8, Nr. 12 (2023): 30777–89. http://dx.doi.org/10.3934/math.20231573.

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<abstract><p>In this study, we deal with the problem of extended dissipativity analysis for memristive neural networks (MNNs) with two-delay components. The goal is to get less conservative extended dissipativity criteria for delayed MNNs. An improved Lyapunov-Krasovskii functional (LKF) with some generalized delay-product-type terms is constructed based on the dynamic delay interval (DDI) method. Moreover, the derivative of the created LKF is estimated using the integral inequality technique, which includes the information of higher-order time-varying delay. Then, sufficient conditions are attained in terms of linear matrix inequalities (LMIs) to pledge the extended dissipative of MNNs via the new negative definite conditions of matrix-valued cubic polynomials. Finally, a numerical example is shown to prove the value and advantage of the presented approach.</p></abstract>
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6

Gao, Xianwen, Lian Lian und Wenhai Qi. „Finite-time dissipativity analysis and design for stochastic Markovian jump systems with generally uncertain transition rates and time-varying delay“. Transactions of the Institute of Measurement and Control 39, Nr. 6 (23.12.2015): 807–19. http://dx.doi.org/10.1177/0142331215620465.

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The paper is concerned with finite-time dissipativity analysis and design for stochastic Markovian jump systems with generally uncertain transition rates and time-varying delay. By constructing a more appropriate Lyapunov–Krasovskii functional, sufficient conditions for finite-time dissipativity of the underlying system are first proposed. Then, a state feedback controller is designed such that the closed-loop Markovian jump system is finite-time dissipative. These sufficient criteria are derived in the form of linear matrix inequalities (LMIs). Finally, numerical examples are given to demonstrate the validity of the main results.
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7

DING, KE, und QING-LONG HAN. „EFFECTS OF COUPLING DELAYS ON SYNCHRONIZATION IN LUR'E COMPLEX DYNAMICAL NETWORKS“. International Journal of Bifurcation and Chaos 20, Nr. 11 (November 2010): 3565–84. http://dx.doi.org/10.1142/s0218127410027908.

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This paper investigates the effects of coupling delays on synchronization in Lur'e complex dynamical networks. Every identical node in the network can be represented as a Lur'e system. Based on Lyapunov–Krasovskii functionals and Lur'e–Postnikov Lyapunov functionals, some delay-dependant synchronization criteria are derived by employing a delay decomposition approach. A Lur'e complex dynamical network with Chua's circuit nodes and one numerical example are given to illustrate the effectiveness of the synchronization criteria.
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8

Manivannan, R., G. Mahendrakumar, R. Samidurai, Jinde Cao und Ahmed Alsaedi. „Exponential stability and extended dissipativity criteria for generalized neural networks with interval time-varying delay signals“. Journal of the Franklin Institute 354, Nr. 11 (Juli 2017): 4353–76. http://dx.doi.org/10.1016/j.jfranklin.2017.04.007.

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9

Phuong, Nguyen Thi, Nguyen Thi Thanh Huyen, Nguyen Thi Huyen Thu, Nguyen Huu Sau und Mai Viet Thuan. „New criteria for dissipativity analysis of Caputo fractional-order neural networks with non-differentiable time-varying delays“. International Journal of Nonlinear Sciences and Numerical Simulation, 06.01.2022. http://dx.doi.org/10.1515/ijnsns-2021-0203.

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Abstract In this article, we investigate the delay-dependent and order-dependent dissipativity analysis for a class of Caputo fractional-order neural networks (FONNs) subject to time-varying delays. By employing the Razumikhin fractional-order (RFO) approach combined with linear matrix inequalities (LMIs) techniques, a new sufficient condition is derived to guarantee that the considered fractional-order is strictly (Q, S, R) − γ − dissipativity. The condition is presented via LMIs and can be efficiently checked. Two numerical examples and simulation results are finally provided to express the effectiveness of the obtained results.
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10

Zhang, Xian-Ming, Qing-Long Han, Xiaohua Ge und Bao-Lin Zhang. „Delay-Variation-Dependent Criteria on Extended Dissipativity for Discrete-Time Neural Networks With Time-Varying Delay“. IEEE Transactions on Neural Networks and Learning Systems, 2021, 1–10. http://dx.doi.org/10.1109/tnnls.2021.3105591.

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Konferenzberichte zum Thema "Delay -dependant dissipativity criteria"

1

Yang, Huilan, Lan Shu, Shouming Zhong und Xin Wang. „New extended dissipativity criteria for distributed delay cellular neural networks“. In 2016 35th Chinese Control Conference (CCC). IEEE, 2016. http://dx.doi.org/10.1109/chicc.2016.7553892.

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