DocumentCode
3264316
Title
Bayesian and Maximum Entropy Approach in Data Processing
Author
Lv, W. ; Tong, L. ; Tian, Y.
Author_Institution
Univ. of Electron. Sci. & Technol. of China, Chengdu
Volume
1
fYear
2006
fDate
25-28 June 2006
Firstpage
344
Lastpage
346
Abstract
The paper discusses the Bayesian maximum entropy approach (Bayesian ME) used in data processing. It is mainly used to solve the probability density function (pdf) in this paper. The contrast has been given out between the Bayesian ME and traditional method. The conclusion has been obtained that the Bayesian ME can get a better estimation of the estimator, and we had better use the higher order of square to get the likelihood function when the specimens are enough
Keywords
Bayes methods; maximum entropy methods; probability; Bayesian maximum entropy approach; data processing; higher order of square; probability density function; Bayesian methods; Data processing; Entropy; Gaussian distribution; Higher order statistics; Information analysis; Lagrangian functions; Paper technology; Probability density function; Statistical distributions;
fLanguage
English
Publisher
ieee
Conference_Titel
Communications, Circuits and Systems Proceedings, 2006 International Conference on
Conference_Location
Guilin
Print_ISBN
0-7803-9584-0
Electronic_ISBN
0-7803-9585-9
Type
conf
DOI
10.1109/ICCCAS.2006.284650
Filename
4063894
Link To Document