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- A novel approach is discussed to choose the bandwidth for kernel density estimation.Based on the Gaussian kernel function, the recursion formula of bandwidth is derived. 摘要在未知总体分布的情形下,给出密度核估计中选择窗宽的一个新方法,并在选取高斯核的情形下,推导出计算窗宽的递归公式。
- Moving object detection based on Gaussian kernel density model 基于高斯核密度模型的运动目标检测
- Gaussian Kernel Density Estimation-based Background Modeling with Noise and Shadow Suppression 高斯核密度估计背景建模及噪声与阴影抑制
- Gaussian kernel density 高斯核密度
- So they have better performance than adaptive Gaussian kernel. 因而,相对于自适应高斯核函数而言,两者性能更优。
- 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。
- This paper improves the adaptive Gaussian kernel (AGK), and presents a novel method for estimating parameters of AGK. 摘要首先分析了自适应高斯核函数的局限性,并作了改进,同时给出了其参数估计方法。
- When the Gaussian kernel function width is 2.0, RVM method possesses more perfect prediction performance. 当高斯核函数的宽度值取为2.;0时,相关向量机方法具有较为理想的预测效果。
- This paper proposes an improvement of LBF model,which utilizes a new kernel function instead of Gaussian kernel function. 提出了一个改进的LBF模型,它使用一个新的核函数代替高斯核函数。
- 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。
- 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。
- A Gaussian kernel adaptive smooth filter is proposed, on the basis of which a scheme is designed to extract information of targets according to the feature that the gray level of point targets and the edge of regional targets are high and vary greatly. 文中提出了高斯核自适应平滑滤波,并在此基础上依据点目标和面目标的边缘灰度值高及变化大的特点设计出提取方法,然后用区域增长恢复没有被提取出来的面目标的内部。
- 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。
- 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。
- 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。
- 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。
- Gaussian kernel with multiple widths 多宽度高斯核
- 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。
- ESTIMATES FOR KERNEL DENSITY OF GENERAL FORM 一般形式的密度估计
- parzen kernel density estimation Parzen核估计