Title :
Aspects of information detection using entropy
Author :
Mrsic-Flögel, Janko
Author_Institution :
Dept. of Comput., Imperial Coll. of Sci., Technol. & Med., London, UK
fDate :
27 Jun-2 Jul 1994
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;
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
DOI :
10.1109/ICNN.1994.374746
