DocumentCode
2364472
Title
Character recognition using class 2 dynamical systems
Author
Liu, Ying
Author_Institution
Dept. of Math. & Comput. Sci., Savannah State Coll., GA, USA
fYear
1993
fDate
25-28 Apr 1993
Firstpage
347
Lastpage
355
Abstract
The author introduces the theory of pattern recognition using class 2 dynamical systems. In particular, the theory of fractal learning is considered, and fractal learning theory is applied to character recognition. Fractal image encoding, that is storing image in stable configurations of dynamical systems, is discussed. Image encoding and decoding algorithms are presented. Several types of fractal equations and their solution are also discussed. Some primary results of fractal learning are demonstrated
Keywords
character recognition; fractals; image coding; learning (artificial intelligence); character recognition; class two dynamical systems; dynamical systems; fractal image decoding; fractal image encoding; fractal learning; Character recognition; Computer science; Educational institutions; Encoding; Equations; Fractals; Image coding; Pattern recognition; Quantization; Uncertainty;
fLanguage
English
Publisher
ieee
Conference_Titel
Uncertainty Modeling and Analysis, 1993. Proceedings., Second International Symposium on
Conference_Location
College Park, MD
Print_ISBN
0-8186-3850-8
Type
conf
DOI
10.1109/ISUMA.1993.366745
Filename
366745
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