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Proceedings Paper

Pattern recognition using w-orbit finite automata
Author(s): Ying Liu; Hede Ma
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Paper Abstract

In this paper, a new pattern recognition scheme is proposed by the authors, which features compressing a huge input vector into a tiny one and catching the characteristics of the input vector efficiently. The development of this scheme is based on a theory of class 2 dynamical systems, where the class 2 dynamical system is defined by the authors. An approach using (omega) -Orbit Finite Automata developed by the authors is a special class of this method. This scheme has two stages, encoding and quantization. The encoding procedure stores an input vector in an attractor of a class 2 dynamical system. The quantization procedure divides the parameter space of the class 2 dynamical systems inferred at encoding stage. A retrieval algorithm for (omega) -OFA and several inference algorithms of class 2 dynamical system from a given input vector are introduced.

Paper Details

Date Published: 1 November 1991
PDF: 15 pages
Proc. SPIE 1606, Visual Communications and Image Processing '91: Image Processing, (1 November 1991); doi: 10.1117/12.50318
Show Author Affiliations
Ying Liu, Savannah State College (United States)
Hede Ma, Savannah State College (United States)

Published in SPIE Proceedings Vol. 1606:
Visual Communications and Image Processing '91: Image Processing
Kou-Hu Tzou; Toshio Koga, Editor(s)

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