《计算机模式识别》是模式识别与智能系统专业硕士研究生的学位课程，它以图象处理技术为基础，研究计算机识别物体的机理，该课程的学习将为计算机视觉以及人工智能等课程的学习打下基础。本课程主要介绍模式识别的基本概念、基本原理、典型方法、实用技术以及有关研究的新成果，其目的是使学生掌握模式识别的基本概念和基本原理，了解模式识别的具体应用、存在的问题和发展前景。主要教学内容包括：（一）统计模式识别，（二）句法模式识别，（三）模糊模式识别；其中统计模式识别又分为：（1）用似然函数进行模式识别；（2）用距离函数机型模式识别；（3）特征选择；句法模式识别又分为：（1）串文法的表达与分类；（2）句法识别；（3）文法推断。

"Pattern Recognition" is the key course for graduate students in the field of pattern recognition and intelligent system. The course studies on object recognition mechanism by computer, which is based on image processing technology and builds the foundation of computer vision and artificial intelligence. The course mainly introduces basic concept, basic principle, typical method, practical technical and related research new achievement of pattern recognition. The main course contents include: (I)statistical pattern recognition, (II)syntax pattern recognition, (III) fuzzy pattern recognition; The Statistical pattern recognition can be divided into: (1) pattern recognition by likelihood function; (2) pattern recognition by distance function; (3) feature choice; The syntax pattern recognition can be divided into: (1) string grammar representation and classification; (2) syntax recognition; (3) grammar inference.