Image Analysis, Random Fields and Markov Chain Monte Carlo Methods: A Mathematical Introduction (Stochastic Modelling and Applied Probability) | 
 enlarge | Author: Gerhard Winkler
Publisher: Springer
Category: Book
List Price: $99.00
Buy New: $74.06
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Rating:  1 reviews
Sales Rank: 902688
Media: Hardcover
Edition: 2nd
Pages: 360
Number Of Items: 1
Shipping Weight (lbs): 1.6
Dimensions (in): 9.3 x 6.3 x 1.1
ISBN: 3540442138
Dewey Decimal Number: 621.367015192
EAN: 9783540442134
Publication Date: February 27, 2006
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Condition: New Book. International Shipping Available
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Product Description
This second edition of G. Winkler's successful book on random field approaches to image analysis, related Markov Chain Monte Carlo methods, and statistical inference with emphasis on Bayesian image analysis concentrates more on general principles and models and less on details of concrete applications. Addressed to students and scientists from mathematics, statistics, physics, engineering, and computer science, it will serve as an introduction to the mathematical aspects rather than a survey. Basically no prior knowledge of mathematics or statistics is required.
The second edition is in many parts completely rewritten and improved, and most figures are new. The topics of exact sampling and global optimization of likelihood functions have been added. This second edition comes with a CD-ROM by F. Friedrich,containing a host of (live) illustrations for each chapter. In an interactive environment, readers can perform their own experiments to consolidate the subject.
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| Customer Reviews:
a bible book to learn Gibbs sampler and simulated annealing July 12, 2000
9 out of 9 found this review helpful
This is absolute a bible book for any person who want to learn Gibbs sampler and simulated annealing seriously. The format of this book, though full of mathematical equations, is very self-evident and concise. Nothing is missing and nothing is redundent. It is an enjoyable journey to follow the logic and principle in this book, with all your attention in. There are full of in-depth discussion in all aspect of the Gibbs sampler, simulated annealing, from the visiting scheme to cooling schedule, and parallel algorithms. The references are excellent too. The author seems to have read all publications till 1995 about this topic and give an excellent detailed and in-depth survey in his book. At the end of your reading, you would have love the mathematical form the author used. Without these tools, many discussions in this book will be just impossible and groundless. I personally have read this book for several times.
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