| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 415349 | Computational Statistics & Data Analysis | 2008 | 19 Pages |
Abstract
The current state of the art in applied decomposition techniques is summarized within a comparative uniform framework. These techniques are classified by the parametric or information theoretic approaches they adopt. An underlying structural model common to all parametric approaches is outlined. The nature and premises of a typical information theoretic approach are stressed. Some possible application patterns for an information theoretic approach are illustrated. Composition is distinguished from decomposition by pointing out that the former is not a simple reversal of the latter. From the standpoint of application to complex systems, a general evaluation is provided.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Computational Theory and Mathematics
Authors
Yalcin Tuncer, Murat M. Tanik, David B. Allison,
