节点文献
利用K-L变换提高模式识别的精度
Pattern recognition improvement using K-L transform
【摘要】 本文采用直接方式和K-L变换方式分别对地震反射信息确定的样本进行了分类。其结果表明:K-L变换前,分类能力不强,而K-L变换后,分辨能力有很大提高,可以更准确地提取到所需样本。此外,K-L变换前,运算速度慢、收敛慢(此处的收敛是指本文以迭代自组织方法聚类时达到需要的类别数);而K-L变换后,运算速度快、收敛也快,且样本数、变量数越多,其优越性越明显。
【Abstract】 The samples of seismic reflection informations are clustered by using direct way and K-L trans form respectively. It can be seen that the clustering is poor before K-L transform, but irnproves greatly after K-L transform to get better samples we need. What is more, K-L transform makes computation and convergence faster than before (The convergence means that we come up to an ideal category number in the case of iterative self-organization clustering)- The more the samples and variables, the more superior the result.
【关键词】 地震反射信息;
K-L变换;
模式识别;
聚类;
精度;
【Key words】 seismic reflection information; K-L transform; pattern recognition; clustering; accuracy;
【Key words】 seismic reflection information; K-L transform; pattern recognition; clustering; accuracy;
- 【文献出处】 石油地球物理勘探 ,Oil Geophysical Prospecting , 编辑部邮箱 ,1995年02期
- 【分类号】P631.4
- 【被引频次】11
- 【下载频次】117