您要查找的是不是：
- 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。
- 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 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。
- 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。
- Gaussian kernel with multiple widths 多宽度高斯核
- 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
- The Comparison between SVM with Gaussian Kernel and Radial Basis Function Classifier 具有高斯核函数的支撑矢量机与径向基函数分类器的比较
- Radial Gaussian Kernel Time-Frequency Distribution and Its Application to Machine Fault Diagnosis 径向高斯核函数时频分布及在故障诊断中的应用
- 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
- Again, the architecture specific kernel code is in arch/*/kernel. 同时与处理器结构相关代码都放在arch／＊／kernel目录下。
- I think there is a kernel of truth in these otherwise frivolous comments. 我认为在这些本来是无关紧要的评论中含有一定的真实性。
- The nutshell includes the kernel. 果壳裹着果仁。
- Zip- Another kind of gaussian elimination zip, C-C. 另一种高斯消去法。
- Hit this area with gaussian blur set to 2. 击中这区域使用高丝模糊2。
- Unconstrained Constant Time Gaussian Blur. 非比例常量时间高斯模糊。
- Remove old kernel image packages. 删除旧的内核映像包。
- Run a Gaussian blur on this layer. 运行高斯模糊就这层。
- He that will eat the kernel must crack the nut. [谚]不劳不获；要想吃果仁，必须破果皮。
