DocumentCode
1306381
Title
Generalized entropy and minimum system complexity
Author
Pandelidis, Ioannis
Author_Institution
Dept. of Mech. Eng., Maryland Univ., College Park, MD, USA
Volume
20
Issue
5
fYear
1990
Firstpage
1234
Lastpage
1238
Abstract
The problem of characterizing information processing systems in terms of their entropic complexity is examined. Automatic control systems and the design/manufacturing process are seen as such systems, so that the results of such research are intended primarily for this area. The concept of generalized entropy is introduced in order to unify the treatment of continuous and discrete signals and the corresponding information processing systems. Given a level of entropic complexity of the reference and disturbance inputs to a system, the author derives minimum entropic complexity requirements for that system. It is assumed that the entropic system complexity that is defined by the author is monotonically related to cost. Based on this assumption and a previously proposed design/manufacturing axiom, the system having minimum entropic complexity is derived
Keywords
control system analysis; information theory; manufacturing processes; design/manufacturing process; entropic complexity; entropy; information processing systems; minimum system complexity; Adaptive systems; Artificial intelligence; Artificial neural networks; Associative memory; Cost accounting; Entropy; Fuzzy logic; Information processing; Learning systems; Neural networks;
fLanguage
English
Journal_Title
Systems, Man and Cybernetics, IEEE Transactions on
Publisher
ieee
ISSN
0018-9472
Type
jour
DOI
10.1109/21.59987
Filename
59987
Link To Document