Title :
Maximum entropy based numerical algorithms for approximation of probability density functions
Author :
Balestrino, A. ; Caiti, A. ; Noe´, A. ; Parenti, F.
Author_Institution :
Dept. Electrical Systems and Automation (DSEA), Univ. of Pisa, Italy
Abstract :
This paper describes several fast algorithms for approximation of the maximum entropy estimate of probability density functions on the basis of a finite number of sampled data. The proposed algorithms are compared with the exact maximum entropy estimate in terms of approximation accuracy and computational efficiency. Some application examples are given.
Keywords :
Approximation algorithms; Approximation methods; Complexity theory; Entropy; Estimation; Probability density function; Standards; Maximum Entropy; Tchebicheff functions; estimation; identification; probability density functions;
Conference_Titel :
European Control Conference (ECC), 2003
Conference_Location :
Cambridge, UK
Print_ISBN :
978-3-9524173-7-9
