该文提出一个有效的基于径向基函数神经网络的模型和状态数据融合的汽轮发电机智能估计方法。
An efficient model based on radial basis function neural network and intelligent estimating method for data fusion of the turbine-generator is presented.
本文系统的介绍了条件随机场的定义、模型结构、特征函数、参数估计及其训练方法等。
This text systematically introduces the definition of CRFs, structure of the CRFs model, feature functions, parameter estimate and training methods.
在二次损失函数下，研究了增长曲线模型误差方差的非齐次二次型估计的可容许性问题。
The admissibility of non-homogeneous quadratic form estimate of variance on the growth curve model was studied under quadratic loss function.
本文研究了一般的随机效应多元线性模型中线性可估函数的最优线性无偏估计。
In this paper we investigated optimal linear unbiased estimation of the linear estimable function in general multivariate random effect linear model.
该方法采用核密度估计模型来构造近似密度函数，利用爬山策略来提取聚类模式。
This method USES kernel density estimation model to construct the approximate density function, and takes hill climbing strategy to extract clustering patterns.
本文讨论了部分变量带误差的线性函数关系模型的参数估计问题。
In this paper, the problem of parameters estimation in linear functional relationship model with "error in some variables" is discussed.
从最新的广义模糊集理论出发建立了一个较为完善的综合评价模型，并提出了残差估计建造评价函数及检验方法。
Based on the theory of generalized fuzzy set, a comprehensive evaluation model has been built, which provides residuals estimate, evaluate function and test methods needed.
给出一种新的组合预测模型——广义加权函数平均组合预测模型及其加权系数的参数估计方法。
In this paper, we present a new kind of combining forecasting model based on the generalized weighted functional mean and the parameter estimation methods of its weighting coefficients.
而后给出了条件随机场的定义、模型结构、势函数的定义、参数估计、训练方法和计算方法等。
Then give the definition of CRFs, model structure, the definition of potential function, parameter estimation, training methods and calculation methods.
提出了一种新的类条件密度函数估计的PNN模型及其算法。
A novel PNN model with training algorithms is proposed for class conditional density estimation.
以线性系统频率响应函数的辨识为研究课题，对系统辨识中所面临的各种干扰噪声对模型精度估计的影响进行了系统的研究。
Serving as the question for study with identification of the frequency response function of the linear system, the effects of noises for estimated accuracy are discussed.
本文首先在介绍了三种教育测量理论的基础上，较详细地论述了项目反应理论的基本原理、模型、参数估计以及信息函数等。
In the thesis, the basic principle, model, parameter estimation and information function of IRT are discussed based on three education test theories.
利用该方法对非线性频响函数进行估计，并利用了最小二乘法对模型的非线性刚度系数和非线性阻尼系数进行了优化。
By which linear and nonlinear frequency response function was estimated, and nonlinear stiffness coefficient and damping coefficient of the model were optimized by least square method in this paper.
神经网络是一个不依赖于模型的自适应函数估计器，不需要模型就可以实现任意的函数关系。
Neural Network is an estimator of adaptive resonance function, which is not dependent on models, and could fulfill arbitrarily functional relation without them.
利用核函数法和广义最小二乘法给出了一般变系数ev模型系数参数的估计，得到了估计的强相合性。
In this paper, the estimation of coefficient functions in a varying-coefficients EV model are constructed by using kernel smoothing and generalized least square method.
基于多项式样条全局光滑方法，建立函数系数线性自回归模型中系数函数的样条估计。
A global smoothing method based on polynomial splines is used to estimate the coefficient functions in functional-coefficient linear autoregressive models.
提出一种优化径向基函数神经网络来波方位(DOA)估计模型结构和参数的方法。
A novel algorithm for optimizing the structure and parameters of Direction of Arrival (DOA) estimation model based on radial basis function neural network is presented.
通过研究尾迹波谱的周期特性与舰船外形特征之间的关系，建立基于波谱函数的舰船长度估计模型。
A close relationship between a ships length and its wakes is presented, and a model is built up based on it.
线性回归模型的误差项不服从正态分布或存在多个离群点时，可以将残差秩次的某些函数作为权重引入估计模型来减少离群点的不良影响。
When multiple outliers occur in linear regression model or the distribution of residuals is not normal, we can use residuals rank as weight function to get some resist estimator.
在建立了样条函数表示载机真实航迹的模型后，采用多测量信号联合估计样条系数的方法实现融合。
We express the true trajectory of the aircraft by means of spline function, and then use measuring data from multichannel to estimate the spline coefficient.
由于PBD算法需要在估计样本函数的同时估计PSF的参数，一般采用的PSF的模型较为复杂，计算量大，收敛慢；
The PBD algorithm needed to simultaneously estimate the specimen function and the parameters of the PSF, while the PSF model was complicated, needed a large number of computation and converged slowly.
本文正是针对该点，提出了一种二维arma模型的初步定阶方法，同时对AR参数的自相关函数估计方法进行了改进，在此基础上得到了功率谱估计算法。
This paper provides a method for the ar order estimation of two dimension ARMA model, and improves an ar parameters estimation method on the basis of autocorrelation function estimation 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.
计算基本SV模型和杠杆效应SV模型的联合特征函数，借助经验特征函数方法估计这两个SV模型。
The characteristic functions of basic SV model and SV model with leverage effect are derived, an estimation (method) of SV models via empirical characteristic function is discussed in this paper.
分析了三种不同的凹函数预测模型，提出了一种适合硬件实现的运动估计快速半像素级搜索算法。
A fast half-pixel motion estimation algorithm is proposed after analyzing three different mathematical prediction models based on concave functions.
给出了一种用于单个复频率估计的陷波器传递函数，并将陷波器模型转换成状态空间模型，此模型具有很好的稳定性。
A notch filter is proposed for single complex frequency estimation problem. It is represented as state-space equation model, which has good stability.
然后结合线性指数模型未知参数在相同损失函数之下的贝叶斯估计得到了未知参数的非参数经验贝叶斯估计。
In combination with the Bayes estimator for the parameter of linear exponential model under the same loss function, the nonparametric empirical Bayes estimator of the unknown parameter was obtained.
文摘：一般线性模型可估函数的可容许估计问题已有详细的讨论。对一般线性模型在矩阵损失下，得到了不可估函数的线性估计为可容许估计的充要条件。
Abstract: Under the matrix loss function, the necessary and sufficient conditions of linear admissible estimates of nonestimatible parameter functions for a general linear model are obtained.
运用广义最小二乘法研究了一类半线性模型中的参数、函数的估计量问题，并证得估计量的一致性结果。
The estimators problem of parameters and functions in Semi-Linear Model were studied by Generalized Least Square method. The agreement between parameters and functional estimators was then presented.
但是这种方法也有不足之处，就在于它对模型有一些弱的假定点估计依赖于误差因子与模型参数的假定，密度估计依赖于误差因子特征函数的假定。
The disadvantages were that this method was based on assumptions on the model: point estimation based on parametric assumption and some properties of error components.
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