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- Objective To explore kerne l density estimate and its applications in analyzing disease. 目的探讨核估计方法及其在小地域分析疾病地图中的应用。
- In this paper, we use several kinds of density estimate, carry on density estimate to line transect sampling of computer simulation. 摘要用几种不同的密度推定法，对测线调查样本进行密度推定。
- Met hods To analyze nasopharyngeal carcinoma death data of Guangdong province Sihui city based on kernel density estimate. 方法利用核密度估计模型,对广东省四会市鼻咽癌死亡资料进行处理。
- Methods Non-parameter kernel density estimation method was adopted. 方法采用非参数核密度估计推断方法。
- Conclusion Kernel density estimate could be used not only for quantitating the spatial distribution of disease,but also for a nalysis of risk factor of disease. 结论核估计方法可以准确定量刻画疾病空间分布特点,有利于进一步对疾病的危险因素研究。
- A natural approach to the construction of contrast function for linear independent component analysis (ICA) is given in this paper based on density estimate with 'semi-parameter'. 摘要基于半参数密度估计给出了构造独立分量分析目标函数的一种方法。
- In this paper,a new crowd density estimation technique is proposed. 论文提出了一种新的人群密度自动估计方法。
- The binned kernel density estimators were exploited to estimate the probability density function of background intensity in training sequence. 该模型采用分箱核密度估计算法从训练图像序列中得到背景的密度函数。
- We produce distance data of the line transect to imitate with 5 density estimations, RRMSE and RB are used to appraise the estimate value and verify their quality. 把5种密度推定法用于计算机模拟产生测线调查的距离数据，由统计量RRMSE和RB对推定值进行评价，来验证其优劣。
- A new stereo matching method based on Kernel Density Estimation(KDE) similarity is proposed. 提出了一种基于核密度估计相似性测度的立体匹配方法。
- non-parametric polynomial density estimate 非参数多项式密度估计
- As the most effective and powerful nonparametric density estimation technique,Kernel Density Estimation（KDE） has been widely analyzed. 摘要 作为当前最先进有效的密度估计算法,核密度估计（KDE）得到了广泛的研究。
- Density estimation technique and hill-climbing strategy are used to define and extract image database clusters and categorization. 然后采用密度估计技术和爬山策略，定义和提取图像数据库的聚类以及归类。
- The algorithm, which consists of two main parts, i.e. the particle tracing and the density estimation with mesh decimation, is described in detail. 算法主要由两个模块组成：粒子跟踪过程，网格优化与密度估计过程，在此进行了详细介绍。
- This thesis is devoted to the study of large deviations for kernel density estimator for certain stochastic processes, especially in the dependent case. 本篇博士论文主要研究随机过程的核密度估计的大偏差,尤其是对相依随机过程,主要结果是首次把独立同分布情形下的大偏差结果推广到了相依情形。
- On the basis of the principle of the linear predictive coding(LPC), an weighting overlaps average LPC power spectrum density estimation algorithm is proposed. 基于线性预测编码(LPC)原理提出了一种加权交叠平均的LPC谱估计算法，同时给出了支持向量机解决多类分类问题的一对多方法。
- On convergence in Lr norm of nonparametric kernel density estimate 非参数核密度估计的Lr收敛
- In this paper laws of the iterated logarithm for quantile density estimator and its derivative estimators areestablished when data are subject to left-truncated and right-censored observations. 对数在左截断右删失数据下;我们基于乘积限估计给出了分位密度估计;获得了分位密度估计及其导数的重对数律.
- This paper proposes a novel moving object segmentation algorithm based on kernel density estimation and edge information to solve the color similarity problem between foreground and background. 摘要针对前景与背景具有相似颜色时的运动对象分割问题，提出一种结合核密度估计和边缘信息的分割算法。
- He was very conservative in the estimate. 他的这一估计很保守。
