DocumentCode
2786595
Title
LSSM based Korean character recognition and colored neural nets
Author
Kim, Sung Tae ; Herath, Susantha
Author_Institution
Dept. of Electr. & Comput. Eng., Drexel Univ., Philadelphia, PA, USA
fYear
1990
fDate
5-7 Sep 1990
Firstpage
333
Lastpage
335
Abstract
The linear systems in a saturated mode (LSSM) model is applied to Korean character recognition. In general, conventional neural networks without uncommitted neurons cannot incorporate new patterns for recognition, and pattern recognition and reconstruction of many learned patterns cannot be performed simultaneously. It is shown that these problems can be solved by using a colored neural net model
Keywords
character recognition; character sets; learning systems; linear systems; neural nets; Korean character recognition; colored neural nets; learned patterns; linear systems in a saturated mode; uncommitted neurons; Character recognition; Computational modeling; Computer science; Differential equations; Linear systems; Machine intelligence; Neural networks; Neurons; Parallel processing; Pattern recognition;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Control, 1990. Proceedings., 5th IEEE International Symposium on
Conference_Location
Philadelphia, PA
ISSN
2158-9860
Print_ISBN
0-8186-2108-7
Type
conf
DOI
10.1109/ISIC.1990.128477
Filename
128477
Link To Document