该决定是基于似然的和潜在的影响。
然后利用最大似然原则得到频偏估计。
Also the frequency offset was estimated based on maximum likelihood (ML) principle.
本文最后一节给出了系统参数的极大似然估计。
In the last section we give the MLE of the parameters in system.
维特比译码算法是卷积编码的最大似然译码算法。
Viterbi algorithm is the most likelihood decode algorithm of convolution code.
其次运用极大似然估计方法对模型的参数进行标定。
And then the model parameters are estimated by means of MLE (maximum likelihood estimation).
本文提出了一种利用广义似然比检测图象边缘的算法。
In this paper, We present an edge detection algorithm using generalized likelihood ratio.
最大似然法采用了迭代的方法来估计噪声的协方差矩。
The estimation of noise covariance matrix is based on iterative procedure in ML.
应用似然比检验和贝叶斯推论进行雉科分子系统学研究。
Both likelihood ratio tests and Bayesian inference are employed to study the phylogeny of Phasianidae.
最大似然法分是常规遥感图像最常用、最有效的分类方法。
Maximum likelihood classifier (MLC) is the most used and effective classification method.
由极大似然估计可以得到单因子利率模型的边际密度函数。
The marginal densities of single-factor interest rate models can be obtained by maximum likelihood estimation.
但是对截尾数据用似然方法的一个问题是MLE可能不存在。
But there is a problem using maximum likelihood estimateit in censored data models, that is MLE may not existence.
论文得到了球形检验的似然比准则，它的渐近展开与极限分布。
The likelihood ratio criterion of sphericity test, its asymptotic expansion and limiting distribution are obtained.
采用了最大平均功率定时同步算法和最大似然载波相位估计算法。
The maximum mean power estimation timing recovery algorithm and the maximum-likelihood carrier phase estimation algorithm are employed.
采用最大似然估计或最大后验概率准则，用估计值来取代前面等式中的真实值。
Either the maximum likelihood estimate or the maximum a posteriori estimate may be used in place of the exact value in the above equations.
但计算很是困难，原因就是删失数据后样本的似然函数的形式很复杂。
But it was difficult to calculate, because censored data in the form of samples of the likelihood function is very complex.
接收端使用最大似然检测器，利用所有接收信号进行多用户联合检测。
The Maximum Likelihood Detector is used in the receiver for joint detection using all received signals.
当保护信息免受非控制访问时，一个新的似然性可能得以应用，即无序。
When information should be protected against non - regulated access a new likelihood could be applied -chaos.
证明了一个分类网络的测试集正确率是该网络推广能力的极大似然估计；
And the accuracy rate of a classification network is explained as the maximum likelihood estimation of the generalization ability.
不分道的最大似然拟合方法和逐事例相关的分辨函数在时间拟合中被采用。
An unbinned maximum likelihood method is used in the lifetime fit with event-by-event resolution functions.
描述最大似然参数估计问题，介绍如何用EM算法求解最大似然参数估计。
We describe the maximum likelihood parameter estimation problem and how the em algorithm can be used for its solution.
计算机模拟表明，在加性高斯噪声下，使用该神经网络可以达到最大似然译码。
The computer simulation shows that the decoder can achieve maximum likelihood decoding in the environmemts of additive white Gaussian noise.
这些编码是四次群最大似然可译分布空时编码，并且功率在中继之间随时间均匀分布。
These codes are four-group ML decodable and have uniform distribution of power among the relays as well as in time.
该方法通过引入目标模型的鲁棒近邻信息以提高在环境不匹配情况下的似然比确认性能。
The method can improve the performance of likelihood ratio verification method in mismatch conditions by incorporating robust neighborhood information for a target model.
首先用参数模型来描述雷达探测信号，然后用最大似然(ml)法对模型参数进行估计。
Using parameter model to describe the radar signals reflective from targets and then the model parameters are estimated by means of ML method.
本文基于信息极大似然估计，采用牛顿迭代算法，建立了ICA的一种信息极大快速算法。
In this paper, proposed is the informax fast algorithm of ICA using information maximum likelihood estimation with the Newton iterate algorithm.
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。
The traditional signal detection theory and method using likelihood ratio test has been used widely, but it has obvious drawbacks.
本文主要讨论在常规雷达低角跟踪中运用波束空间域最大似然（BDML）估计的实现技术。
This paper proposes a BDML estimator used for low angle tracking in conventional radar.
利用该矩阵良好的正交性发射的信号，在接受端可以通过简单的最大似然解码算法来准确还原。
By the orthogonality of symbols, a simple maximum likelihood-decoding algorithm is used to recover them at the receiver accurately.
利用该矩阵良好的正交性发射的信号，在接受端可以通过简单的最大似然解码算法来准确还原。
By the orthogonality of symbols, a simple maximum likelihood-decoding algorithm is used to recover them at the receiver accurately.
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