DocumentCode :
2167977
Title :
An associative memory model for unsupervised sequence processing
Author :
Pantazi, Stefan V. ; Moehr, Jochen R.
Author_Institution :
Sch. of Health Inf. Sci., Victoria Univ., BC, Canada
fYear :
2005
fDate :
24-26 Aug. 2005
Firstpage :
233
Lastpage :
236
Abstract :
We introduce the design principles and present formally the building block of an associative memory model capable of unsupervised sequence processing: the constrained partially ordered set. We then use the model in a series of experiments, presented in increasing order of complexity and conclude that it demonstrates interesting information processing capabilities which warrant future development.
Keywords :
information theory; associative memory model; unsupervised sequence processing; Associative memory; Computational modeling; Computer science; Distributed processing; Fasteners; Information processing; Information retrieval; Information science; Information theory; Probability distribution;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Communications, Computers and signal Processing, 2005. PACRIM. 2005 IEEE Pacific Rim Conference on
Print_ISBN :
0-7803-9195-0
Type :
conf
DOI :
10.1109/PACRIM.2005.1517268
Filename :
1517268
Link To Document :
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