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Random Motions in Markov and SemiMarkov Random Environments 2

This book is the second of two volumes on random motions in Markov and semi-Markov random environments. This second volume focuses on high;

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Random Motions in Markov and SemiMarkov Random Environments 1

This book is the first of two volumes on random motions in Markov and semi-Markov random environments. This first volume focuses on;

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Random Walks Of Infinitely Many Particles

The author's previous book, Random Walk in Random and Non-Random Environments, was devoted to the investigation of the Brownian motion of a;

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Markov Random Flights

dimensions. Markov random flights is a stochastic dynamic system subject to the control of an external Poisson process and represented by the;

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Stochastic Analysis for Gaussian Random Processes and Fields

random fields indexed by measures and generalized Gaussian random fields indexed by Schwartz space. The Markov property for generalized random;

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Stochastic Analysis for Gaussian Random Processes and Fields

indexed by measures and generalized Gaussian random fields indexed by Schwartz space. The Markov property for generalized random fields;

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Random Processes For Engineers

This engaging introduction to random processes provides students with the critical tools needed to design and evaluate engineering systems;

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Random Dynamical Systems

of irreducible Markov processes, especially Markov chains, is surveyed in Chapter 2. Equilibrium and long run stability of a dynamical system in which;

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Random Dynamical Systems

of irreducible Markov processes, especially Markov chains, is surveyed in Chapter 2. Equilibrium and long run stability of a dynamical system in which;

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Markov Chains

Markov chains are central to the understanding of random processes. This is not only because they pervade the applications of random;

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Markov Random Field Modeling in Image Analysis

Markov random field (MRF) theory provides a basis for modeling contextual constraints in visual processing and interpretation. It enables;

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Stability and Stabilization of Nonlinear Systems with Random Structures

systematic treatment of stability theory and the theory of stabilization of nonlinear systems with random structure in terms of new developments;

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Probability An Introduction 2Nd

account of the basic features of probability and random processes at the level of first and second year mathematics undergraduates and Masters;

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Random Matrices And Random Partitions

, martingale differences sequences and Markov chains, etc. These classical theorems are frequently used in the study of random matrices and random;

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Hybrid Random Fields

of Bayesian networks and Markov random fields, the newly introduced hybrid random fields are an interesting approach to get the best of both these;

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Statistical Inference for Piecewise-deterministic Markov Processes

, neuroscience, networks, finance... Such processes are defined by a deterministic motion punctuated by random jumps at random times, and offer simple;

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Markov-modulated Processes And Semiregenerative Phenomena

The book presents a coherent treatment of Markov random walks and Markov additive processes together with their applications. Part I;

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A First Course in Probability and Markov Chains

in Probability and Markov Chains presents an introduction to the basic elements in probability and focuses on two main areas. The first part explores;

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Products of Random Variables

functions Probes sequences of prime divisors and prime numbers Discusses Markov chains, Hilbert spaces, and quotients of random variables;

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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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Probability and Random Processes

; multiple random variables; random sequences and series; random processes in linear systems; Markov processes; and power spectral density.

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Probability for Engineering, Mathematics, and Science, International Edition

well as the how of probability distributions for random variables to help engage readers and further promote their understanding. In addition;

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Gaussian Markov Random Fields

Gaussian Markov Random Field (GMRF) models are most widely used in spatial statistics - a very active area of research in which few up-to;

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Gaussian Markov Random Fields

Gaussian Markov Random Field (GMRF) models are most widely used in spatial statistics - a very active area of research in which few up-to;

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Elementary Applications of Probability Theory

the weak law of numbers. The next four chapters introduce random processes, including random walks and Markov chains illustrated by examples;

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Elementary Applications of Probability Theory

the weak law of numbers. The next four chapters introduce random processes, including random walks and Markov chains illustrated by examples;

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