Results for 'Stochastic stability'

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  1.  61
    Stochastic Stability and Disagreements between Dynamics.Aydin Mohseni - 2019 - Philosophy of Science 86 (3):497-521.
    The replicator dynamics and Moran process are the main deterministic and stochastic models of evolutionary game theory. The models are connected by a mean-field relationship—the former describes the expected behavior of the latter. However, there are conditions under which their predictions diverge. I demonstrate that the divergence between their predictions is a function of standard techniques used in their analysis and of differences in the idealizations involved in each. My analysis reveals problems for stochastic stability analysis in (...)
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  2.  18
    Stability Analysis of Impulsive Stochastic Reaction-Diffusion Cellular Neural Network with Distributed Delay via Fixed Point Theory.Ruofeng Rao & Shouming Zhong - 2017 - Complexity:1-9.
    This paper investigates the stochastically exponential stability of reaction-diffusion impulsive stochastic cellular neural networks. The reaction-diffusion pulse stochastic system model characterizes the complexity of practical engineering and brings about mathematical difficulties, too. However, the difficulties have been overcome by constructing a new contraction mapping and an appropriate distance on a product space which is guaranteed to be a complete space. This is the first time to employ the fixed point theorem to derive the stability criterion of (...)
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  3.  28
    Stochastic properties of stabilized-image binocular rivalry alternations.R. Randolph Blake, Robert Fox & Curtis McIntyre - 1971 - Journal of Experimental Psychology 88 (3):327.
  4.  32
    Stochastic gene expression stabilization as a new therapeutic strategy for cancer.Jean-Pascal Capp - 2012 - Bioessays 34 (3):170-173.
    Graphical AbstractCurrent differentiation therapies for cancer may not be effective because it might not be enough to only use molecules targeting chromatin remodelers. It may also be necessary to stabilize the re-expressed genes to convert malignant cells into benign ones.
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  5.  7
    Stochastically Globally Exponential Stability of Stochastic Impulsive Differential Systems with Discrete and Infinite Distributed Delays Based on Vector Lyapunov Function.Xiaoyan Liu & Quanxin Zhu - 2020 - Complexity 2020:1-16.
    This paper deals with stochastically globally exponential stability for stochastic impulsive differential systems with discrete delays and infinite distributed delays. By using vector Lyapunov function and average dwell-time condition, we investigate the unstable impulsive dynamics and stable impulsive dynamics of the suggested system, and some novel stability criteria are obtained for SIDSs with DDs and IDDs. Moreover, our results allow the discrete delay term to be coupled with the nondelay term, and the infinite distributed delay term to (...)
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  6.  25
    Exponential stability for markovian jumping stochastic BAM neural networks with mode-dependent probabilistic time-varying delays and impulse control.R. Rakkiyappan, A. Chandrasekar, S. Lakshmanan & Ju H. Park - 2015 - Complexity 20 (3):39-65.
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  7.  16
    Stability of a Stochastic Model of an SIR Epidemic with Vaccination.P. J. Witbooi - 2017 - Acta Biotheoretica 65 (2):151-165.
    We prove almost sure exponential stability for the disease-free equilibrium of a stochastic differential equations model of an SIR epidemic with vaccination. The model allows for vertical transmission. The stochastic perturbation is associated with the force of infection and is such that the total population size remains constant in time. We prove almost sure positivity of solutions. The main result concerns especially the smaller values of the diffusion parameter, and describes the stability in terms of an (...)
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  8.  11
    Stability and cooperative solution in stochastic games.Elena M. Parilina & Alessandro Tampieri - 2018 - Theory and Decision 84 (4):601-625.
    This paper analyses the principles of stable cooperation for stochastic games. Starting from the non-cooperative version of a discounted, non zero-sum stochastic game, we build its cooperative form and find the cooperative solution. We then analyse the conditions under which this solution is stable. Principles of stability include subgame consistency, strategic stability and irrational behaviour proof of the cooperative solution. We finally discuss the existence of a stable cooperative solution, and consider a type of stochastic (...)
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  9.  9
    Robust Stabilization of Stochastic Markovian Jump Systems with Distributed Delays.Guilei Chen, Zhenwei Zhang, Chao Li, Dianju Qiao & Bo Sun - 2021 - Complexity 2021:1-8.
    This paper addresses the robust stabilization problem for a class of stochastic Markovian jump systems with distributed delays. The systems under consideration involve Brownian motion, Markov chains, distributed delays, and parameter uncertainties. By an appropriate Lyapunov–Krasovskii functional, the novel delay-dependent stabilization criterion for the stochastic Markovian jump systems is derived in terms of linear matrix inequalities. When given linear matrix inequalities are feasible, an explicit expression of the desired state feedback controller is given. The designed controller, based on (...)
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  10.  26
    Stability criteria for stochastic Takagi-Sugeno fuzzy Cohen-Grossberg BAM neural networks with mixed time-varying delays.Muhammed Syed Ali, Pagavathigounder Balasubramaniam, Fathalla A. Rihan & Shanmugam Lakshmanan - 2016 - Complexity 21 (5):143-154.
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  11.  32
    Robust stability analysis of stochastic neural networks with Markovian jumping parameters and probabilistic time-varying delays.Chandrasekar Pradeep, Arunachalam Chandrasekar, Rangasamy Murugesu & Rajan Rakkiyappan - 2016 - Complexity 21 (5):59-72.
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  12.  9
    Stability Analysis of the Bat Algorithm Described as a Stochastic Discrete-Time State-Space System.Janusz Piotr Paplinski - 2018 - Complexity 2018:1-10.
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  13.  15
    Exponential Stabilization of Coupled Hybrid Stochastic Delayed BAM Neural Networks: A Periodically Intermittent Control Method.Yunjian Peng, Birong Zhao, Weijie Sun & Feiqi Deng - 2018 - Complexity 2018:1-14.
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  14.  30
    Multiple-interval-dependent robust stability analysis for uncertain stochastic neural networks with mixed-delays.Jianwei Xia, Ju H. Park & Hao Shen - 2016 - Complexity 21 (1):147-162.
  15.  22
    Finite-time stability of fractional-order stochastic singular systems with time delay and white noise.Kalidass Mathiyalagan & Krishnan Balachandran - 2016 - Complexity 21 (S2):370-379.
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  16.  15
    Stochastic gene expression, disruption of tissue averaging effects and cancer as a disease of development.Jean-Pascal Capp - 2005 - Bioessays 27 (12):1277-1285.
    Despite the extensive literature describing the somatic genetic alterations in cancer cells, the precise origins of cancer cells remain controversial. In this article, I suggest that the etiology of cancer and the generation of genetic instability in cancer cells should be considered in the light of recent findings on both the stochastic nature of gene expression and its regulation at tissue level. By postulating that gene expression is intrinsically probabilistic and that stabilization of gene expression arises by cellular interactions (...)
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  17.  18
    Tissue‐disruption‐induced cellular stochasticity and epigenetic drift: Common origins of aging and cancer?Jean-Pascal Capp & Frédéric Thomas - 2021 - Bioessays 43 (1):2000140.
    Age‐related and cancer‐related epigenomic modifications have been associated with enhanced cell‐to‐cell gene expression variability that characterizes increased cellular stochasticity. Since gene expression variability appears to be highly reduced by—and epigenetic and phenotypic stability acquired through—direct or long‐range cellular interactions during cell differentiation, we propose a common origin for aging and cancer in the failure to control cellular stochasticity by cell–cell interactions. Tissue‐disruption‐induced cellular stochasticity associated with epigenetic drift would be at the origin of organ dysfunction because of an increase (...)
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  18. Stability criteria for the contextual emergence of macrostates in neural networks.Adam Barrett & Harald Atmanspacher - unknown
    More than thirty years ago, Amari and colleagues proposed a statistical framework for identifying structurally stable macrostates of neural networks from observations of their microstates. We compare their stochastic stability criterion with a deterministic stability criterion based on the ergodic theory of dynamical systems, recently proposed for the scheme of contextual emergence and applied to particular inter-level relations in neuroscience. Stochastic and deterministic..
     
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  19.  31
    The Foundations of Linear Stochastic Electrodynamics.L. De la Peña & A. M. Cetto - 2006 - Foundations of Physics 36 (3):350-368.
    An analysis is briefly presented of the possible causes of the failure of stochastic electrodynamics (SED) when applied to systems with nonlinear forces, on the basis that the main principles of the theory are correct. In light of this analysis, an alternative approach to the theory is discussed, whose postulates allow to establish contact with quantum mechanics in a natural way. The ensuing theory, linear SED, confirms the essential role of the vacuum–particle interaction as the source of quantum phenomena.
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  20. Stability of risk preferences and the reflection effect of prospect theory.Manel Baucells & Antonio Villasís - 2010 - Theory and Decision 68 (1-2):193-211.
    Are risk preferences stable over time? To address this question we elicit risk preferences from the same pool of subjects at two different moments in time. To interpret the results, we use a Fechner stochastic choice model in which the revealed preference of individuals is governed by some underlying preference, together with a random error. We take cumulative prospect theory as the underlying preference model (Kahneman and Tversky, Econometrica 47:263–292, 1979; Tversky and Kahneman, Journal of Risk and Uncertainty 5:297–323, (...)
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  21. Thermal stability of solitons in protein α-helices.Danko D. Georgiev & James F. Glazebrook - 2022 - Chaos, Solitons and Fractals 155:111644.
    Protein α-helices provide an ordered biological environment that is conducive to soliton-assisted energy transport. The nonlinear interaction between amide I excitons and phonon deformations induced in the hydrogen-bonded lattice of peptide groups leads to self-trapping of the amide I energy, thereby creating a localized quasiparticle (soliton) that persists at zero temperature. The presence of thermal noise, however, could destabilize the protein soliton and dissipate its energy within a finite lifetime. In this work, we have computationally solved the system of (...) differential equations that govern the quantum dynamics of protein solitons at physiological temperature, T=310 K, for either a single isolated α-helix spine of hydrogen bonded peptide groups or the full protein α-helix comprised of three parallel α-helix spines. The simulated stochastic dynamics revealed that although the thermal noise is detrimental for the single isolated α-helix spine, the cooperative action of three amide I exciton quanta in the full protein α-helix ensures soliton lifetime of over 30 ps, during which the amide I energy could be transported along the entire extent of an 18-nm-long α-helix. Thus, macromolecular protein complexes, which are built up of protein α-helices could harness soliton-assisted energy transport at physiological temperature. Because the hydrolysis of a single adenosine triphosphate molecule is able to initiate three amide I exciton quanta, it is feasible that multiquantal protein solitons subserve a variety of specialized physiological functions in living systems. (shrink)
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  22.  10
    Asynchronous Stabilization of Nonlinear Markov Jump Singularly Perturbed Systems via Fuzzy Static Output Feedback Control.Baogang Ding, Tingting Ma, Xiaoxin Feng & Yueying Wang - 2021 - Complexity 2021:1-10.
    This study focuses on the static output feedback control of nonlinear Markov jump singularly perturbed systems within the framework of Takagi–Sugeno fuzzy approximation. From a practical point of view, the phenomenon of asynchronous switching between the plant and the controller is considered and characterized by a finite piecewise-homogenous Markov process. Particularly, for facilitating the controller synthesis, the closed-loop system is transformed into a fuzzy Markov jump singularly perturbed descriptor system by adopting descriptor representation. In order to fully accommodate the system (...)
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  23.  10
    No Impact of Stochastic Galvanic Vestibular Stimulation on Arterial Pressure and Heart Rate Variability in the Elderly Population.Akiyoshi Matsugi, Koji Nagino, Tomoyuki Shiozaki, Yohei Okada, Nobuhiko Mori, Junji Nakamura, Shinya Douchi, Kosuke Oku, Kiyoshi Nagano & Yoshiki Tamaru - 2021 - Frontiers in Human Neuroscience 15:646127.
    ObjectiveNoisy galvanic vestibular stimulation (nGVS) is often used to improve postural stability in disorders, such as neurorehabilitation montage. For the safe use of nGVS, we investigated whether arterial pressure (AP) and heart rate vary during static supine and slow whole-body tilt with random nGVS (0.4 mA, 0.1–640 Hz, gaussian distribution) in a healthy elderly population.MethodsThis study was conducted with a double-blind, sham-controlled, cross-over design. Seventeen healthy older adults were recruited. They were asked to maintain a static supine position on (...)
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  24.  12
    Modeling and Dynamic Analysis in a Hybrid Stochastic Bioeconomic System with Double Time Delays and Lévy Jumps.Chao Liu, Longfei Yu & Luping Wang - 2018 - Complexity 2018:1-23.
    A double delayed hybrid stochastic prey-predator bioeconomic system with Lévy jumps is established and analyzed, where commercial harvesting on prey and environmental stochasticity on population dynamics are considered. Two discrete time delays are utilized to represent the maturation delay of prey and gestation delay of predator, respectively. For a deterministic system, positivity of solutions and uniform persistence of system are discussed. Some sufficient conditions associated with double time delays are derived to discuss asymptotic stability of interior equilibrium. For (...)
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  25.  22
    Dynamical Analysis of Two-Microorganism and Single Nutrient Stochastic Chemostat Model with Monod-Haldane Response Function.Mengnan Chi & Wencai Zhao - 2019 - Complexity 2019:1-13.
    In this paper, we formulate and investigate a two-microorganism and single nutrient chemostat model with Monod-Haldane response function and random perturbation. First, for the corresponding deterministic system, we introduce the conditions of the stability of the equilibrium points. Then, using Lyapunov function and Itô’s formula, we investigate the existence and uniqueness of the global positive solution of the stochastic chemostat model. Furthermore, we explore and obtain the criterions of the extinction and the permanence for the stochastic model. (...)
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  26.  10
    Stationary Distribution and Periodic Solution of Stochastic Toxin-Producing Phytoplankton–Zooplankton Systems.Chunjin Wei & Yingjie Fu - 2020 - Complexity 2020:1-15.
    In this paper, we investigate the dynamics of autonomous and nonautonomous stochastic toxin-producing phytoplankton–zooplankton system. For the autonomous system, we establish the sufficient conditions for the existence of the globally positive solution as well as the solution of population extinction and persistence in the mean. Furthermore, by constructing some suitable Lyapunov functions, we also prove that there exists a single stationary distribution which is ergodic, what is more important is that Lyapunov function does not depend on existence and (...) of equilibrium. For the nonautonomous periodic system, we prove that there exists at least one nontrivial positive periodic solution according to the theory of Khasminskii. Finally, some numerical simulations are introduced to illustrate our theoretical results. The results show that weaker white noise and/or toxicity will strengthen the stability of system, while stronger white noise and/or toxicity will result in the extinction of one or two populations. (shrink)
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  27.  78
    Adaptive Event-Triggered Control for Complex Dynamical Network with Random Coupling Delay under Stochastic Deception Attacks.M. Mubeen Tajudeen, M. Syed Ali, Syeda Asma Kauser, Khanyaluck Subkrajang, Anuwat Jirawattanapanit & Grienggrai Rajchakit - 2022 - Complexity 2022:1-12.
    This study concentrates on adaptive event-triggered control of complex dynamical networks with unpredictable coupling delays and stochastic deception attacks. The adaptive event-triggered mechanism is used to avoid the wasting of limited bandwidth. The probability of data communicated by the network is established by statistical properties and Bernoulli stochastic variables with an uncertain occurrence probability. Stability analysis based on Lyapunov–Krasovskii functional and the stability of the closed-loop system is guaranteed. Using the LMI technique, we obtain triggered parameters. (...)
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  28.  76
    Backstepping Output Feedback Control for the Stochastic Nonlinear System Based on Variable Function Constraints with the Subsea Intelligent Electroexecution Robot System.Long-Chuan Guo, Jing Ni, Jing-Biao Liu, Xiang-Kun Fang, Qing-Hua Meng & Yu-Dong Peng - 2021 - Complexity 2021:1-15.
    The output feedback controller is designed for a class of stochastic nonlinear systems that satisfy uncertain function growth conditions for the first time. The multivariate function growth condition has greatly relaxed the restrictions on the drift and diffusion terms in the original stochastic nonlinear system. Here, we cleverly handle the problem of uncertain functions in the scaling process through the function maxima theory so that the Ito differential system can achieve output stabilization through Lyapunov function design and the (...)
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  29.  7
    Solvency Evaluation Model of Insurance Company Based on Stochastic Differential Equation.Kai Wang & Ling Zhu - 2021 - Complexity 2021:1-12.
    Solvency assessment is the core content of insurance supervision. In this paper, from the perspective of capital flow, the insurance company’s capital flow is regarded as a dynamic system, the stochastic differential equations model is established to describe its flow characteristics, and the existence of positive equilibrium point of the system is proved, as well as the conditions of stability at equilibrium point, that is, the requirements of the insurance company’s solvency. Furthermore, by using the numerical simulation method, (...)
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  30.  9
    Generating Functional and Quantum Stability in Field Theory Models with Solitons.L. Roszkowski - 1984 - In Heinrich Mitter & Ludwig Pittner (eds.), Stochastic Methods and Computer Techniques in Quantum Dynamics. Springer Verlag. pp. 427--433.
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  31. Valore morale e società nel pensiero di Eugène Dupréel.Giampiero Stabile - 1976 - [Salerno]: A cura del Centro stampa dell'Università.
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  32.  8
    L'esperienza della natura: pensiero scientifico e disincantamento del mondo da Aristotele a Leopardi.Giorgio Stabile - 2023 - Firenze: SISMEL - Edizioni del Galluzzo. Edited by Franco D'Intino.
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  33. Kurt W. Schmidt.Stabilizing or Changing Identity? The Ethical - 2002 - In Julia Lai Po-Wah Tao (ed.), Cross-Cultural Perspectives on the (Im) Possibility of Global Bioethics. Kluwer Academic.
     
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  34.  52
    John Courtney Murray and the Abortion Debate.Susan J. Stabile - 2007 - Journal of Catholic Social Thought 4 (1):87-124.
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  35. La ruota della fortuna: tempo ciclico e ricorso storico.Giorgio Stabile - 1979 - Studi Filosofici 2:93.
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  36. Lo scetticismo e Montaigne.Giampiero Stabile - 1980 - In Ida Cappiello (ed.), Privato, società civile e potere: momenti della costituzione critica della ragione borghese: [scritti. Napoli: Liguori.
     
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  37.  24
    “Poor” Coverage.Susan J. Stabile - 2008 - Journal of Catholic Social Thought 5 (1):125-160.
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  38.  16
    “Poor” Coverage.Susan J. Stabile - 2008 - Journal of Catholic Social Thought 5 (1):125-160.
  39.  29
    Subsidiarity and the Use of Faith-Based Organizations in the Fight against Poverty.Susan J. Stabile - 2005 - Journal of Catholic Social Thought 2 (2):313-368.
  40.  30
    Vocation, Formation and the Next Generation.Susan J. Stabile - 2010 - Journal of Catholic Social Thought 7 (2):439-466.
  41.  14
    Workers in the Vineyard.Susan J. Stabile - 2008 - Journal of Catholic Social Thought 5 (2):371-411.
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  42.  32
    Workers in the Vineyard.Susan J. Stabile - 2008 - Journal of Catholic Social Thought 5 (2):371-411.
  43. Jeremy Butterfield.Outcome Dependence & Stochastic Einstein Nonlocaljty - 1994 - In Dag Prawitz & Dag Westerståhl (eds.), Logic and Philosophy of Science in Uppsala. Kluwer Academic Publishers. pp. 385.
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  44.  22
    Improving the Design of Intelligent Systems: Outstanding Problems and Some Solutions.L. J. Kohout & I. Stabile - 1998 - Journal of Intelligent Systems 8 (3-4):225-238.
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  45.  13
    Stable individual differences in unfamiliar face identification: Evidence from simultaneous and sequential matching tasks.K. A. Baker, V. J. Stabile & C. J. Mondloch - 2023 - Cognition 232 (C):105333.
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  46.  39
    Cycles versus equilibrium in evolutionary games.Thomas W. L. Norman - 2010 - Theory and Decision 69 (2):167-182.
    Mixed-strategy equilibria are typically rather unstable in evolutionary game theory. “Monocyclic” games, such as Rock–Paper–Scissors, have only mixed equilibria, some of which are “stable” in the sense that sequential best replies lead to them; yet, even these games are prone to stable cycles under discrete-time simultaneous best replies, giving an unusual equilibrium-selection problem. This article analyzes such games in a random-utility setting where changing strategies is costly, and the speed of the dynamic is, thus, endogenous. The stochastically stable outcome is (...)
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  47. Follow the leader : local interactions with influence neighborhoods.Peter Vanderschraaf & J. McKenzie Alexander - 2005 - Philosophy of Science 72 (1):86-113.
    We introduce a dynamic model for evolutionary games played on a network where strategy changes are correlated according to degree of influence between players. Unlike the notion of stochastic stability, which assumes mutations are stochastically independent and identically distributed, our framework allows for the possibility that agents correlate their strategies with the strategies of those they trust, or those who have influence over them. We show that the dynamical properties of evolutionary games, where such influence neighborhoods appear, differ (...)
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  48.  10
    Sampling-Based Event-Triggered Control for Neutral-Type Complex-Valued Neural Networks with Partly Unknown Markov Jump and Time-Varying Delay.Zhen Wang, Lianglin Xiong, Haiyang Zhang & Yingying Liu - 2021 - Complexity 2021:1-21.
    This work is devoted to studying the stochastic stabilization of a class of neutral-type complex-valued neural networks with partly unknown Markov jump. Firstly, in order to reduce the conservation of our stability conditions, two integral inequalities are generalized to the complex-valued domain. Secondly, a state-feedback controller is designed to investigate the stability of the neutral-type CVNNs with H ∞ performance, making the stability problem a further extension, and then, the stabilization of the CVNNs with H ∞ (...)
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  49.  13
    Robust Observer Design for Discrete Descriptor Systems with Packet Losses.Yan Liu, Weifeng Zhong, Qiang Fan, Bo You & Jiazhong Xu - 2021 - Complexity 2021:1-11.
    This paper considers observer design for discrete-time descriptor systems with packet losses. By taking packet loss into consideration, the error dynamic of the proposed observer becomes a stochastic switched system. Consequently, the proposed observer is synthesized in a stochastic switched system framework. Sufficient conditions for the stochastic stability with a prescribed robust performance of the error dynamic system are derived and converted into linear matrix inequalities. Not only can the proposed observer deal with packet losses, but (...)
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  50.  51
    Follow the leader : local interactions with influence neighborhoods. [REVIEW]Marc Ereshefsky, Mohan Matthen, Matthew H. Slater, Alex Rosenberg, D. M. Kaplan, Kevin Js Zollman, Peter Vanderschraaf, J. McKenzie Alexander & Gordon Belot - 2005 - Philosophy of Science 72 (1):86-113.
    We introduce a dynamic model for evolutionary games played on a network where strategy changes are correlated according to degree of influence between players. Unlike the notion of stochastic stability, which assumes mutations are stochastically independent and identically distributed, our framework allows for the possibility that agents correlate their strategies with the strategies of those they trust, or those who have influence over them. We show that the dynamical properties of evolutionary games, where such influence neighborhoods appear, differ (...)
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