DocumentCode
2708872
Title
Design of unsupervised classifier
Author
Sayeh, M.R. ; Ragu, A. ; Szu, H.H.
Author_Institution
Dept. of Electr. Eng., Southern Illinois Univ., Carbondale, IL, USA
fYear
1991
fDate
8-14 Jul 1991
Firstpage
417
Abstract
Reports a feedback unsupervised classifier formulated by differential equations with no external control and few tuning parameters. This classifier is called the Lyapunov associative memory, in order to emphasize the importance of the Lyapunov (energy) function in the design of the associative memory. A vigilance parameter is built in to the dynamics of the classifier. Its architecture consists of two modules: the learning and recall modules. The learning module shapes the recall module, energy function with the arrival of new input information. The classifier was tested with an analog input pattern used by the ART-2 (adaptive resonance theory) model
Keywords
Lyapunov methods; classification; content-addressable storage; differential equations; feedback; learning systems; neural nets; pattern recognition; ART-2; Lyapunov associative memory; adaptive resonance theory; analog input pattern; differential equations; dynamics; energy function; feedback unsupervised classifier; learning module; recall module; vigilance parameter; Associative memory; Equations; Feedback; Magnesium compounds; Shape; Silver; Springs; Stability; Subspace constraints; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1991., IJCNN-91-Seattle International Joint Conference on
Conference_Location
Seattle, WA
Print_ISBN
0-7803-0164-1
Type
conf
DOI
10.1109/IJCNN.1991.155369
Filename
155369
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