1) likelihood rate test
似然率检测
2) likelihood ratio test
似然比检测
1.
According to the model,a generalized likelihood ratio test rule was developed for the target identification,and then the analytical expression to calculate the target identification performance was theoretically given.
为了实现发射周期内目标的实时识别,首先建立了E脉冲激励下目标回波的二元假设检验模型,在此基础上导出了识别目标的广义似然比检测量,并从理论上给出了计算目标识别概率的解析表达式。
2.
First pretreat image through high pass or morphologic filtering, then progress likelihood ratio test to segment possible targets from the image.
首先通过高通或形态学滤波进行图像预处理 ,进一步用似然比检测分割出候选目标 ,考虑到环境干扰造成的目标在某一帧暂时消失的情况 ,提出了利用目标运动特征通过选择合适的邻域判决条件并结合图像流分析提取运动弱小目标的一种方法。
3.
A quasi-hybrid likelihood ratio test (qHLRT) classifier is proposed for linear modulation classification,with unknown carrier frequency offsets (CFO).
针对存在未知载波频偏(CFO)的线性调制分类,提出一种混合似似然比检测(qHLRT)分类器。
3) detection likelihood ratio
检测似然比
1.
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。
4) maximum likelihood detection
最大似然检测
1.
It is proved that when the transmit- ted signals are PSK modulated,the optimal maximum likelihood detection algorithm under perfect or imperfect channel estimation is equivalent to the conventional zero-forcing detection algorithm.
研究结果表明,当发送信号为 PSK 调制方式时,无论是理想信道估计还是非理想信道估计,最大似然检测算法与传统的迫零检测算法等价。
5) GLRT
广义似然比检测
1.
Based on the temporal difference models for background noise pixel,target pixel and clutter pixel,we formulate the detection problem in 2 steps,correlation detection and generalized likelihood ratio test(GLRT).
在图像序列中背景像素、目标像素以及杂波像素的时域差分模型基础上提出了红外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。
2.
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。
6) ML Detection
最大似然检测
1.
Based on the combination of modified iterative QR decomposition (ZFCD#*2MIQRD) and maximum likelihood (ML) detection, the paper represents a new combined detection algorithm which obtains transmission sign vectors,n_T evaluations, by ZFCD#*2MIQRD, and then searches for the optimized adjudgment vector for n_T evaluation vectors by ML detection algorithm.
结合迭代QR分解和最大似然检测提出一种新的联合检测算法。
补充资料：极大似然估计
极大似然估计法是求估计的另一种方法。它最早由高斯提出。后来为费歇在1912年的文章中重新提出，并且证明了这个方法的一些性质。极大似然估计这一名称也是费歇给的。这是一种上前仍然得到广泛应用的方法。它是建立在极大似然原理的基础上的一个统计方法，极大似然原理的直观想法是：一个随机试验如有若干个可能的结果A，B，C，%26#8230;。若在一次试验中，结果A出现，则一般认为试验条件对A出现有利，也即A出现的概率很大。
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条