摘要
研究了统计模式识别研究的主要新进展。介绍了统计模式识别的原理和方法。从类条件概率分布的估计、线性判别法、贝叶斯分类器、误差界以及新的模式识别模型等方面概述了近几年有关统计模式识别方面的研究进展。最后进行了评述。
Major recent developments of statistical pattern recognition are reviewed First, the principle and methods of statistical pattern recognition are described Then, the newly research of statistical pattern recognition is reviewed, which consists of class-conditional-density estimation,linear discriminant methods,Bayes classifier,error bounds and some novel pattern recognition models Finally, some comments about pattern recognition are commented
出处
《军民两用技术与产品》
2003年第11期39-42,共4页
Dual Use Technologies & Products
关键词
统计模式识别
线性判别法
贝叶斯分类器
误差界
支持向量机
神经网络
粗糙集
Pattern recognition,Statistical pattern recognition,Neural networks,Support vector machines,Class-conditional-density estimation,Iinear discriminant methods,Bayes classifier,Kernel function based methods,Rough sets
