Pattern recognition using ω-orbit finite automata
Ying Liu, H. Ma · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1991
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.