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Linear Stochastic Systems

Linear Stochastic Systems, originally published in 1988, is today as comprehensive a reference to the theory of linear discrete-time;

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Advanced Topics in Control and Estimation of State-Multiplicative Noisy Systems

of reduced-order and preview tracking control are also presented and solved. The second part of the monograph concerns non-linear stochastic state;

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Stochastic Stability of Differential Equations in Abstract Spaces

and biological problems. Its core material is divided into three parts devoted respectively to the stochastic stability of linear systems, non;

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Time Series Analysis

, Time Series Analysis provides an accessible yet thorough introduction to the methods for modeling linear stochastic systems. It will help you;

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Stochastic Processes

This book contains examples of Stochastic Processes. It shows how to work with them. Specifically, it shows how to calculate the Mean;

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Advances in the Control of Markov Jump Linear Systems with No Mode Observation

Markov jump linear systems (MJLS). It also presents an algorithm that attempts to solve this open stochastic control problem, and provides a real;

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Optimal Networked Control Systems with MATLAB

design of stochastic adaptive controllers for a class of linear and nonlinear systems Presents two-player zero-sum game-theoretic;

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Optimal Networked Control Systems With MATLAB

of stochastic adaptive controllers for a class of linear and nonlinear systems Presents two-player zero-sum game-theoretic formulation for linear;

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Parametric Random Vibration

Coherent and systematic, this text explores the behavior of linear and nonlinear dynamical systems subject to parametric random vibrations;

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Stochastic Game Strategies and their Applications

problems, which are stimulated by a vast number of applications. This book addresses the gap to discuss general stochastic n-person noncooperative;

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Stochastic Game Strategies and their Applications

problems, which are stimulated by a vast number of applications. This book addresses the gap to discuss general stochastic n-person noncooperative;

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Dynamical Mechanical Systems Under Random Impulses

devised to characterize the response of linear and nonlinear mechanical systems as the solutions of underlying stochastic differential equations;

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Communication Systems

and stochastic processes and their applications to the analysis of linear systems Includes five appendices covering Fourier series and;

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Communication Systems

and stochastic processes and their applications to the analysis of linear systems Includes five appendices covering Fourier series and;

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Communication Systems

and stochastic processes and their applications to the analysis of linear systems Includes five appendices covering Fourier series and;

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Stochastic Dynamics

of stochastic variables and stochastic processes have been indicated. Chapter 4 deals with the stochastic response analysis of single degrees;

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Recent Advances in Inverse Scattering, Schur Analysis and Stochastic Processes

, moment problems, random matrices and linear stochastic systems.;

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Recent Advances in Inverse Scattering, Schur Analysis and Stochastic Processes

, moment problems, random matrices and linear stochastic systems.;

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Linear Systems

Balancing rigorous theory with practical applications, Linear Systems: Optimal and Robust Control explains the concepts behind linear;

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Formal Modeling and Analysis of Timed Systems

stochastic approaches to real-time, including monitoring and Big Data; timed systems; linear and non-linear systems; timed automata; special session;

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Stochastic Control of Partially Observable Systems

The problem of stochastic control of partially observable systems plays an important role in many applications. All real problems are;

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Fractional Signals and Systems

discrete derivatives, and the corresponding linear systems. Both time and frequency analysis are presented. Some advanced topics are included like;

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Quasilinear Control

design of linear plant or nonlinear instrumentation (LPNI) systems. The approach of QLC is based on the method of stochastic linearization, which;

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Quasilinear Control

design of linear plant or nonlinear instrumentation (LPNI) systems. The approach of QLC is based on the method of stochastic linearization, which;

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Discovering Evolution Equations with Applications

(ODEs) and extends the theory to systems of homogenous linear stochastic ODEs. The next several chapters focus on abstract homogenous linear;

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Discovering Evolution Equations with Applications

(ODEs) and extends the theory to systems of homogenous linear stochastic ODEs. The next several chapters focus on abstract homogenous linear;

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Stochastic Networked Control Systems: Stabilization and Optimization Under Information Constraints

a supplemental graduate text. The reader is expected to have some familiarity with linear systems, stochastic processes, and Markov chains;

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