DocumentCode
288790
Title
Aspects of information detection using entropy
Author
Mrsic-Flögel, Janko
Author_Institution
Dept. of Comput., Imperial Coll. of Sci., Technol. & Med., London, UK
Volume
5
fYear
1994
fDate
27 Jun-2 Jul 1994
Firstpage
3196
Abstract
An evolving learning system should be able to self-organise on its input vector continuously through time. This paper presents initial simulation results which show that entropy is a measure which could be employed to find various coding structure information by inspection of a binary input channel through time. It also shows that source information needs to be sparsely coded for entropy to be able to detect which code bitstring lengths are being employed to communicate source information to a self-organizing system
Keywords
entropy codes; information theory; learning systems; self-adjusting systems; binary input channel; coding structure information; entropy; evolving learning system; information detection; input vector; self-organizing system; source information; Communication channels; Computational modeling; Educational institutions; Entropy; Fault tolerance; Humans; Inspection; Learning systems; Sense organs; Time measurement;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on
Conference_Location
Orlando, FL
Print_ISBN
0-7803-1901-X
Type
conf
DOI
10.1109/ICNN.1994.374746
Filename
374746
Link To Document