Abstract: In this paper, the learning principle of qualitative mapping model is given, orthogonality space of qualitative mapping is put forward. Fourier transformation is induced by orthogonality space. After that, the real meaning of property calculation is discussed, and the pattern recognition method based on the orthogonality space of qualitative mapping is bring forward. Some actual applications using such method are given in the end.

Key words: Qualitative mapping, Machine learning, Orthogonality space of QM, Pattern recognition

摘要： 给出了定性映射模型的学习机制，然后提出了定性映射正交基空间的概念，在此正交基空间下诱导出了傅立叶变换，并解释了从数值计算到属性计算的内涵，提出定性映射正交基空间下的模式识别技术。最后给出了该方法的应用实例。

关键词: 定性映射, 机器学习, 定性映射正交基空间, 模式识别

CLC Number: 

• TP391