## Dynamic Probabilistic Systems: Volume I: Markov Models by Ronald A. Howard
This comprehensive manual provides a rigorous introduction to the theory of Markov models, essential for understanding and analyzing dynamic probabilistic systems. Ideal for researchers and practitioners in various fields, including engineering, operations research, computer science, and economics.
**Key Features:**
* **In-depth coverage:** Covers the fundamental concepts and techniques of Markov models in a comprehensive manner.
* **Rigorous mathematical framework:** Provides a solid mathematical foundation for understanding the theory and its applications.
* **Numerous examples and problems:** Illustrates key concepts and helps readers develop practical skills.
* **Applications across disciplines:** Explores applications of Markov models in engineering, operations research, computer science, and economics.
* **Advanced topics:** Includes advanced topics such as Markov decision processes, hidden Markov models, and Kalman filters.
**Table of Contents:**
* **Introduction**
* What are Markov models?
* Applications of Markov models
* **Discrete-Time Markov Chains**
* Basic concepts
* Transition probabilities
* Steady-state analysis
* **Continuous-Time Markov Chains**
* Definition and properties
* Birth-death processes
* Queueing systems
* **Markov Decision Processes**
* Decision-making under uncertainty
* Value iteration
* Policy improvement
* **Hidden Markov Models**
* Modeling hidden states
* Inference algorithms
* **Kalman Filters**
* State estimation
* Linear dynamic systems
* Optimal filtering
**Benefits:**
* Gain a thorough understanding of the theory of Markov models.
* Develop skills in applying Markov models to solve real-world problems.
* Stay up-to-date with the latest developments in dynamic probabilistic modeling.
**Target Audience:**
* Researchers and practitioners in engineering, operations research, computer science, and economics.
* Students seeking a comprehensive introduction to Markov models.
* Professionals looking to enhance their understanding of dynamic probabilistic systems.
An integrated work in two volumes, this text teaches readers to formulate, analyze, and evaluate Markov models. The first volume treats basic process; the second, semi-Markov and decision processes. 1971 edition.
Author: Howard, Ronald A.
Publisher: Dover Publications
Illustration: N
Language: ENG
Title: Dynamic Probabilistic Systems, Volume I: Markov Models
Pages: 00608 (Encrypted EPUB)
On Sale: 2012-04-06
SKU-13/ISBN: 9780486458700
Category: Mathematics : Probability & Statistics - General
