The Experts below are selected from a list of 87 Experts worldwide ranked by ideXlab platform
Chen Naihui - One of the best experts on this subject based on the ideXlab platform.
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the representation of finite fourier series for Conditional Mathematical Expectation of discrete random variable
Journal of Guangxi Teachers Education University, 2008Co-Authors: Chen NaihuiAbstract:When distribution function of random variable X is N order uniform step,the obtained results in the paper are as follows,(1)the representation of Fourier series for function of random variable f(X);(2) the representation of Fourier series for Conditional Mathematical Expectation E(Y|X).
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the expansion of trigonometric polynomial series for Conditional Mathematical Expectation and function of random variable
Journal of Sichuan Normal University, 2007Co-Authors: Chen NaihuiAbstract:The obtained results in the paper are as follows:(1) the expansion of Fourier series of orthogonal trigonometric polynomial for Conditional Mathematical Expectation and function of random variable;(2) the best approximation of trigonometric polynomial about another random variable for function of a random variable;(3) the best approximation order of trigonometric polynomial for function of random variable.
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constructive representation for Conditional Mathematical Expectation
Journal of Beijing University of Technology, 2006Co-Authors: Chen NaihuiAbstract:The purpose of this paper is to study the structure on GDnditional Mathematical Expectation E(Y| X1,..., Xm ) . If (X1,..., Xm ) is independent continuously, first it is ascertained that measurable function set of (X1,..., Xm ) is a Hilbert space, and a normal orthogonal basis of the space is gained. Then it is brought to light that the linear structure on GDnditional Mathematical Expectation is E ( Y | X1,..., Xm ) =
B. P. Kharlamov - One of the best experts on this subject based on the ideXlab platform.
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Characteristic operator and the curvilinear integral for a semi-Markov process
Journal of Soviet Mathematics, 1992Co-Authors: B. P. KharlamovAbstract:The connection between the characteristic operator and the Lévy representation of the Conditional generating function of the first exit time of a semi-Markov process is considered. The absolutely continuous part of Lévy's additive functional is expressed in the form of a curvilinear integral of the value of the characteristic operator of unity with respect to the Conditional Mathematical Expectation of the traversal time relative to sequences of states. The obtained formula is used for a new derivation of the linearity of the characteristic operator for a Markov process.
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Characteristic operator and the curvilinear integral for a semi-Markov process
Journal of Mathematical Sciences, 1992Co-Authors: B. P. KharlamovAbstract:The connection between the characteristic operator and the Levy representation of the Conditional generating function of the first exit time of a semi-Markov process is considered. The absolutely continuous part of Levy's additive functional is expressed in the form of a curvilinear integral of the value of the characteristic operator of unity with respect to the Conditional Mathematical Expectation of the traversal time relative to sequences of states. The obtained formula is used for a new derivation of the linearity of the characteristic operator for a Markov process.
Kan-jian Zhang - One of the best experts on this subject based on the ideXlab platform.
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Exponential $H_{\infty}$ Filter Design for Discrete Time-Delay Stochastic Systems With Markovian Jump Parameters and Missing Measurements
IEEE Transactions on Circuits and Systems I: Regular Papers, 2011Co-Authors: Feipeng Da, Kan-jian ZhangAbstract:In this paper, the exponential H∞ filtering problem is studied for discrete time-delay stochastic systems with Markovian jump parameters and missing measurements. The measurement missing phenomenon, which is related to the modes of subsystems, is described in the form of random matrix function and the missing probability of each sensor at every mode is governed by an individual random variable taking values in the interval [0,1] . This description of missing measurements is more general than the existing ones, where the missing probability is described by a Bernoulli distribution white sequence or a certain diagonal matrix. By using Lyapunov method and the properties of Conditional Mathematical Expectation, we propose a novel approach to achieve the delay-dependent exponential stability criterion such that the filtering error system is mean-square exponentially stable and satisfies a prescribed H∞ performance level. Moreover, there is no equation restriction on decay rate. Then, based on the obtained sufficient criterion, the filter matrices can be directly characterized by solving a set of linear matrix inequalities (LMIs). Finally, a numerical example is provided to show the validity of the main result.
Feipeng Da - One of the best experts on this subject based on the ideXlab platform.
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Exponential $H_{\infty}$ Filter Design for Discrete Time-Delay Stochastic Systems With Markovian Jump Parameters and Missing Measurements
IEEE Transactions on Circuits and Systems I: Regular Papers, 2011Co-Authors: Feipeng Da, Kan-jian ZhangAbstract:In this paper, the exponential H∞ filtering problem is studied for discrete time-delay stochastic systems with Markovian jump parameters and missing measurements. The measurement missing phenomenon, which is related to the modes of subsystems, is described in the form of random matrix function and the missing probability of each sensor at every mode is governed by an individual random variable taking values in the interval [0,1] . This description of missing measurements is more general than the existing ones, where the missing probability is described by a Bernoulli distribution white sequence or a certain diagonal matrix. By using Lyapunov method and the properties of Conditional Mathematical Expectation, we propose a novel approach to achieve the delay-dependent exponential stability criterion such that the filtering error system is mean-square exponentially stable and satisfies a prescribed H∞ performance level. Moreover, there is no equation restriction on decay rate. Then, based on the obtained sufficient criterion, the filter matrices can be directly characterized by solving a set of linear matrix inequalities (LMIs). Finally, a numerical example is provided to show the validity of the main result.
Weihai Zhang - One of the best experts on this subject based on the ideXlab platform.
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Robust $H_\infty$ Filtering for Nonlinear Discrete-time Stochastic Systems
arXiv: Optimization and Control, 2018Co-Authors: Tianliang Zhang, Feiqi Deng, Weihai ZhangAbstract:This paper mainly discusses the $H_{\infty}$ filtering of general nonlinear discrete time-varying stochastic systems. A nonlinear discrete-time stochastic bounded real lemma (SBRL) is firstly obtained by means of the smoothness of the Conditional Mathematical Expectation, and then, based on the given SBRL and a stochastic LaSalle-type theorem, a sufficient condition for the existence of the $H_\infty$ filtering of general nonlinear discrete time-varying stochastic systems is presented via a new introduced Hamilton-Jacobi inequality (HJI), which is easily verified. When the worst-case disturbance $\{v^*_k\}_{k\in {\mathcal N}}$ is considered, the suboptimal $H_2/H_\infty$ filtering is studied. Two examples including a practical engineering example show the effectiveness of our main results.