Maximum Entropy and Bayesian Methods: Santa Fe, New Mexico, U.S.A., 1995 : Proceedings of the Fifteenth International Workshop on Maximum Entropy and Bayesian Methods

Hanson, Kenneth M. (Editor) / Silver, Richard N. (Editor)

ISBN 10: 0792343115 / ISBN 13: 9780792343110

Published by Springer, 1996

About this Item

480 pages. 10.00x6.75x1.25 inches. In Stock.

Seller Inventory # x-0792343115

Bibliographic Details

• Title: Maximum Entropy and Bayesian Methods: Santa Fe, New Mexico, U.S.A., 1995 : Proceedings of the Fifteenth International Workshop on Maximum Entropy and Bayesian Methods
• Publisher: Springer
• Publication Date: 1996
• Language: English
• ISBN 10: 0792343115
• ISBN 13: 9780792343110
• Binding: Hardcover
• Condition: Brand New
• Weight: 1.01 kilograms

About this title

Synopsis

This volume contains the proceedings of the Fifteenth International Workshop on Maximum Entropy and Bayesian Methods, held in Sante Fe, New Mexico, USA, from July 31 to August 4, 1995.
Maximum entropy and Bayesian methods are widely applied to statistical data analysis and scientific inference in the natural and social sciences, engineering and medicine. Practical applications include, among others, parametric model fitting and model selection, ill-posed inverse problems, image reconstruction, signal processing, decision making, and spectrum estimation. Fundamental applications include the common foundations for statistical inference, statistical physics and information theory. Specific sessions during the workshop focused on time series analysis, machine learning, deformable geometric models, and data analysis of Monte Carlo simulations, as well as reviewing the relation between maximum entropy and information theory.
Audience: This book should be of interest to scientists, engineers, medical professionals, and others engaged in such topics as data analysis, statistical inference, image processing, and signal processing.

From the Back Cover

This volume contains the proceedings of the Fifteenth International Workshop on Maximum Entropy and Bayesian Methods, held in Santa Fe, New Mexico, U.S.A., from July 31-August 4, 1995. Maximum entropy and Bayesian methods are widely applied to statistical data analysis and scientific inference in the natural and social sciences, engineering and medicine. Practical applications include, among others, parametric model fitting and model selection, ill-posed inverse problems, image reconstruction signal processing, decision making, and spectrum estimation. Fundamental applications include the common foundations for statistical inference, statistical physics and information theory. Specific sessions during the workshop focused on time series analysis, machine learning, deformable geometric models, and data analysis of Monte Carlo simulations, as well as reviewing the relation between maximum entropy and information theory. Audience: This book should be of interest to scientists, engineers, medical professionals, and others engaged in such topics as data analysis, statistical inference, image processing, and signal processing.