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Stochastic Modeling and Analysis of Telecom Networks

as Markov processes, real and spatial point processes and stochastic recursions, and presenting a wide list of results on stability;

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Markov Processes and Applications

, Professor at Universite de Paris-Orsay, France. Markov processes is the class of stochastic processes whose past and future are conditionally;

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Markov Chains & Stochastic Stability

Meyn and Tweedie is back! The bible on Markov chains in general state spaces has been brought up to date to reflect developments in the;

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Structured Stochastic Matrices of M/G/1 Type and Their Applications

This book deals with Markov chains and Markov renewal processes (M/G/1 type). It discusses numerical difficulties which are apparently;

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Ergodic Behavior of Markov Processes

stochastic differential equations helps in a deeper understanding of specific examples. Contents Part I: Ergodic Rates for Markov Chains;

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Markov Processes for Stochastic Modeling

parameters. A Markov chain is a stochastic process characterized by the Markov prop erty that the distribution of future depends only on the current;

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Topics in the Constructive Theory of Countable Markov Chains

Markov chains are an important idea, related to random walks, which crops up widely in applied stochastic analysis. They are used, for;

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Topics in the Constructive Theory of Countable Markov Chains

Markov chains are an important idea, related to random walks, which crops up widely in applied stochastic analysis. They are used, for;

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Finite Markov Processes and Their Applications

A self-contained treatment of finite Markov chains and processes, this text covers both theory and applications. Author Marius Iosifescu;

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Selected Topics on Continuous-Time Controlled Markov Chains and Markov Games

of stochastic control problems in which a single decision-maker wishes to optimize a given objective function. This book is also concerned with Markov;

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Stochastic Modeling in Physical and Biological Sciences

of Markov Chains. This book elaborates continuous time stochastic processes for modeling purpose explaining in detail with examples and includes an;

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Elements of Applied Stochastic Processes

This 3rd edition of the successful Elements of Applied Stochastic Processes improves on the last edition by condensing the material and;

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Markov Chains

art of stochastic modeling, shows how to design computer implementations, and provides extensive worked examples with case studies. Markov;

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Stochastic Analysis and Applications in Physics

the mathematics of Markov processes and the physics of quantum systems. The deterministic-stochastic interface is addressed, as are Euclidean;

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Elements Of Stochastic Modelling

This textbook has been developed from the lecture notes for a one-semester course on stochastic modelling. It reviews the basics;

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Introduction to the Numerical Solution of Markov Chains

A cornerstone of applied probability, Markov chains can be used to help model how plants grow, chemicals react, and atoms diffuse--and;

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Stochastic Models With Applications To Genetics, Cancers, Aids And Other Biomedical Systems

to Markov chains through stochastic difference equations and stochastic differential equations. It illustrates how these processes and;

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Martingales and Markov Chains

A thorough grounding in Markov chains and martingales is essential in dealing with many problems in applied probability, and is a gateway;

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Martingales and Markov Chains

A thorough grounding in Markov chains and martingales is essential in dealing with many problems in applied probability, and is a gateway;

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Modeling and Analysis of Stochastic Systems

Building on the author's more than 35 years of teaching experience, Modeling and Analysis of Stochastic Systems, Third Edition, covers the;

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Modeling and Analysis of Stochastic Systems

Building on the author's more than 35 years of teaching experience, Modeling and Analysis of Stochastic Systems, Third Edition, covers the;

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Asymptotic Properties of Permanental Sequences

in stochastic processes, infinitely divisible processes and Markov chains.;

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Studies in the Theory of Random Processes

chapters explore the theory of stochastic differential equations, permitting the construction of a broad class of Markov processes on the basis;

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Asymptotic Analyses for Complex Evolutionary Systems with Markov and Semi-Markov Switching Using Approximation Schemes

This book analyzes stochastic evolutionary models under the impulse of diffusion, as well as Markov and semi-Markov switches. Models are;

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Introduction to Hidden Semi-Markov Models

Markov chains and hidden Markov chains have applications in many areas of engineering and genomics. This book provides a basic introduction;

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Stochastic Models With Applications to Genetics, Cancers, AIDS, and Other Biomedical Systems

to Markov chains through stochastic difference equations and stochastic differential equations. It illustrates how these processes and;

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Elements of Stochastic Modelling

This is the expanded second edition of a successful textbook that provides a broad introduction to important areas of stochastic modelling;

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