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Elsevier Markov Processes for Stochastic Modeling Book

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Description

Explore the fundamental principles of Markov processes with this comprehensive text from Elsevier. This book explains how Markov processes function as systems with limited memory, where dependence on the past is determined solely through the previous state. This resource provides a detailed look at how these processes model various real-world systems. It covers a wide range of applications including communications systems, transportation networks, and image segmentation. Readers will find insights into biological systems, DNA sequence analysis, and random atomic motion. The text also addresses practical uses in social mobility, population studies, epidemiology, and animal migration. For those in technical fields, it covers queueing systems, resource management, financial engineering, actuarial science, and decision systems.

Key Features

This Elsevier publication covers Markov processes, which are systems defined by limited memory and dependence on previous states.

The text provides modeling applications for communications systems and transportation networks.

Learn how to apply these mathematical processes to image segmentation, analysis, and biological systems.

The book includes details on DNA sequence analysis, random atomic motion, and diffusion in physics.

Explore stochastic modeling for social mobility, population studies, epidemiology, and animal or insect migration.

Technical applications include queueing systems, resource management, dams, and financial engineering.

This resource is designed for studies in actuarial science and complex decision systems.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
03 June 2016
Listed Since
24 December 2013

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