Generalized maximum likelihood ratio detection algorithm (GLR) is a typical method of space-time adaptive signal processing.
狭义最大似然比检测算法(GLR)非空时自逆当信号处放的比拟典型的算法。
In this paper, We present an edge detection algorithm using generalized likelihood ratio.
本文提出了一种利用广义似然比检测图象边缘的算法。
The traditional signal detection theory and method using likelihood ratio test has been used widely, but it has obvious drawbacks.
传统信号检测理论和方法主要采用似然比检测，已得到广泛的应用，但是存在明显的缺点。
Based on the characteristics of the detection likelihood ratio sequence and the recursive relations, a fast algorithm is proposed.
文中根据检测似然比序列的特点，利用递推关系，提出了一种快速算法。
On the basis of studying the algorithms of network traffic abnormality detection, an improved Generalized Likelihood Ratio (IGLR) algorithm is proposed.
在研究分析了几种网络流量异常检测算法的基础上，提出了一种改进的广义似然估计（IGLR）的检测算法。
Then based on the temporal difference models, we formulate the detection problem in 2 steps, correlation detection and generalized likelihood ratio test (GLRT).
然后基于时域差分模型提出了红外慢速小目标时域检测算法，算法共分为两步：相关检测和广义似然比检测。
Based on the likelihood ratio test theory, a new detection statistic is proposed in this paper for monitoring the machine tool cutting chatter development.
根据似然比检验原理提出了一种新的机床切削颤振监测统计量，能识别切削过程中产生的信噪比为0.15的微弱振动成份。
Based on the likelihood ratio test theory, a new detection statistic is proposed in this paper for monitoring the machine tool cutting chatter development.
根据似然比检验原理提出了一种新的机床切削颤振监测统计量，能识别切削过程中产生的信噪比为0.15的微弱振动成份。
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