Attribute network computing based on qualitative mapping and its application in pattern recognition

Abstract

It is shown in this paper that a qualitative mapping model of pattern recognition can be induced by the basic princeple that the pattern P({(x $_{j}$ , y'(x $_{j}$ )}) constructed by the set of the pair of varibale x $_{j}$ and its computing value y'(x $_{j}$ ) of a function y = f(x) could be considered as the graph of y(x), and a logic circuit, called Attribute Network Computing can be constructed by the relation between the input and output of qualitative mapping, such that not only a lot of artificial intelligent methods, such as Expert Syatem, Artificial Neural Network, and Support Vector Machine can be fused and unified in it, but also a lot of pattern recognition can be implemented by it.