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