统计模式识别（Statistic Pattern Recognition）是对模式的统计分类方法，即把模式类看成是用某个随机向量实现的 集合，又称为决策理论识别方法。
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Modulation recognition methods presented for single signal case are not valid for multiple signals' case, including decision theory based and statistic pattern recognition based methods.
已有的调制识别方法，包括基于决策理论的方法和基于统计模式识别的方法，绝大多数都是针对单信号提出的，不能直接用于多信号的识别。
In this paper, the problem of statistic pattern recognition converted into the problem of the best hypothesis test of risk which can be used to judge whether the machine is in normal operation or not.
本文将统计图形识别问题转化为风险的最佳假设检验问题，并用之于对机器运行是否正常的判断。
Measuring the segmented image by statistic method to obtain morphological and location features of the target, which provides info for intelligent understanding and pattern recognition;
对分割的结果进行测量，应用图像统计学的方法获得了目标图像的一系列形状位置特征参数，为进一步的树木图像理解和模式识别做准备；
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