A novel speaker adaptation method named maximum likelihood model interpolation (MLMI) is proposed.
本文提出了一种新的说话人自适应算法———最大似然模型插值。
This text establishes a model of space-time block code system at first, and also introduces the theory of maximum likelihood estimate.
文章首先建立了空时分组编码的系统模型，并且介绍了最大似然估计的理论。
The tendency check, goodness of fit check, maximum likelihood estimates (MLE) of the parameters and MTBF for AMSAA model are presented.
给出了趋势检验、AMSAA模型的拟合优度检验及模型参数的极大似然估计方法。
A model and an algorithm were provided for constructing phylogenetic tree based on the principle of maximum likelihood estimate.
利用最大似然估计原理，给出了构建系统发生树的模型和算法。
The model parameters were estimated by a maximum likelihood algorithm, which maximizes the likelihood of the observed data.
采用最大似然估计算法，对模型中的隐含参数进行了估计。
In comparison with the maximum likelihood classification by field survey data, the classification precision of this model heightens 16%.
结合实地调查数据与最大似然分类算法进行对比实验，表明该模型比最大似然总体分类精度高16%。
As to the estimating process of GARCH (1, 1) model, the author adopted Maximum Likelihood Estimation and BHHH algorithm to get unknown parameters' value.
至于GARCH(1,1)模型的估计过程，本文用最大似然估计法和BHHH算法求未知参数值。
Using the mixture distribution model and the method of maximum likelihood, we developed the method for the genetic analysis of qualitative quantitative traits with use of DH and RIL data.
采用混合分布理论与极大似然法，拓展了适用于双单倍体群体（DH）和重组近交系（RIL）群体的质量-数量性状的遗传分析方法。
The latter since include maximum likelihood estimate of the GPD(generalized Pareto distribution ) model parameters to still include moment estimate etc.
后者既包括基于广义帕雷托分布（GPD）参数的极大似然估计，又包括矩法估计等。
Firstly, we introduce the theory of finite mixture model and EM algorithm for maximum likelihood estimation.
首先，介绍了有限混合模型理论及应用EM算法求解极大似然估计。
In order to enhance the fault tolerance ability of the fault diagnosis model, information correction is thus adopted based on the maximum likelihood decoding theory.
为了提高模型的容错性，提出了基于最大似然译码原理的监测信号信息校正方法，然后利用编码基本网在无畸变信号的基础上进行故障诊断。
We often estimate the return model parameter by ordinary least squares and maximum likelihood.
对回归模型进行参数估计时，常用的两种重要方法是普通最小二乘法和最大似然法。
The training of the novel model utilizes the maximum likelihood criterion and an effective EM algorithms to adjust model parameters is developed.
新模型的训练采用最大似然准则，并改进了EM算法来调整模型参数。
And then the model parameters are estimated by means of MLE (maximum likelihood estimation).
其次运用极大似然估计方法对模型的参数进行标定。
The parameters in model are estimated by maximum likelihood estimate method.
利用最大似然估计法对模型中的参数进行了估计。
The parameters in model were estimated by maximum likelihood estimate method.
利用最大似然估计法对模型中的参数进行了估计。
The model is based on different semantic relationships, and is estimated according to maximum likelihood estimation. Semantic distance is used to estimate semantic relationships in estimating period.
该模型定义在不同语义关系之上，基于极大似然估计法利用语义距离来对语义关系进行参数估计。
Conclusion the maximum likelihood method based on MCECM algorithm can be used to estimate the parameters of non-linear factor analysis model.
结论基于MCECM算法的极大似然估计方法可用于估计非线性因子分析模型的参数。
The paper estimates both the static and dynamic versions of the model by using simulated maximum likelihood techniques.
文章使用模拟最大似然值方法估计了静态与动态模型。
Furthermore, through the maximum likelihood used for evaluating three parameters of wavelet coefficients' probability model, the adaptive algorithm is derived in the article.
而且本文通过极大似然法估计小波系数概率模型中的三个参数，使算法达到自适应。
We formalize this intuition by specifying a model of web browsing behavior and then deriving the maximum likelihood estimate of a user's social profile.
我们正式通过指定这个直觉的网页浏览行为模型，然后推导的极大似然估计一个用户的社会形象。
Furthermore, by evaluating three parameters of wavelet coefficients "probability model using maximum likelihood method, self adaptively of the algorithm is achieved."
而且通过极大似然法估计小波系数概率模型中的三个参数，使算法达到自适应性。
This model function is applied to NSCAT data to retrieve wind vectors, with the Maximum-Likelihood Estimator to get a set of ambiguous wind vectors and a vector filter technique to remove ambiguities.
利用该模式函数对另一组NSCAT后向散射系数数据进行海面风场反演，采用最大似然估计确定多个风矢量解，并采用矢量中值滤波消除多解。
When errors is a ar (1) time series, we studied the quasi-likelihood equation for the semiparametric model, and investigated the existence of quasi-maximum likelihood estimators.
在误差为AR(1)时间序列的情形下，给出了半参数回归模型的拟极大似然估计方程，并研究了拟极大似然估计量的存在性。
The parameters of Fisher distribution model are estimated by maximum likelihood, and the model is finally verified by using Pearson test.
利用所提出的快速聚类分析方法及其推导的计算公式，可以方便地求解费歇尔分布的参数。
Parameters of the model are measured by a linear regression technique and a maximum likelihood method.
在因子范围服从对数正态分布下，应用线性回归技术和极大似然法建立了模型参数的测定方法。
The parameters of model are measured by taking into account the stochastic characteristic of entire test data, which is connected with a maximum likelihood method and math programming.
考虑整套试验数据的随机特性，利用极大似然法原理和数学规划法求解模型参数。
In this paper, a method of process quality diagnosis using hypothesis testing for residual sequence of ARMA innovation model estimation error by recursive maximum likelihood method was studied.
本文基于辨识 ARMA新息模型生成估计残差序列 ，再对残差序列的平均值和无偏方差进行假设检验 ，可实现工序质量的异常诊断。
In this paper, a method of process quality diagnosis using hypothesis testing for residual sequence of ARMA innovation model estimation error by recursive maximum likelihood method was studied.
本文基于辨识 ARMA新息模型生成估计残差序列 ，再对残差序列的平均值和无偏方差进行假设检验 ，可实现工序质量的异常诊断。
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