Markov Random Fields and Their Applications

Markov Random Fields and Their Applications



File : pdf, 7 MB, 133 pages

by Ross Kindermann and J. Laurie Snell – AMS Books

Markov random fields is a new branch of probability theory that promises to be important both in the theory and application of probability. The existing literature on the subject is quite technical and often only understandable to the expert. This paper is an attempt to present the basic ideas of the subject and its application to a wider audience.

1. The Ising Model

2. Markov Fields on Graphs

3. Finite Lattices

4. Dynamic Models

5. The Tree Model

6. Additional Applications

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