Selection of bandwidth type and adjustment side in kernel density estimation over inhomogeneous backgrounds

2010 ◽  
Vol 24 (5) ◽  
pp. 643-660 ◽  
Author(s):  
Xun Shi
Keyword(s):  
Density Estimation ◽  
Kernel Density Estimation ◽  
Kernel Density ◽  
Selection Of

The Feature Description Method of Radar Signal Based on Improved Kernel Density Estimation

2013 ◽  
Vol 380-384 ◽  
pp. 3501-3504
Author(s):  
Fei Ye ◽  
Jie Zhou ◽  
Jun Luo ◽  
Xing Rong Gao
Keyword(s):  
Density Estimation ◽  
Kernel Density Estimation ◽  
Kernel Density ◽  
Estimation Algorithm ◽  
Radar Signal ◽  
Sample Distribution ◽  
Feature Description ◽  
Feature Based ◽  
Selection Of ◽  
Probability Density Curve

According to the problem that the existing radar signal feature cannot effectively express and analysis its characteristic, a description method of radar emitter signal feature based on improved kernel density estimation is proposed. This improved kernel density estimation algorithm combine the selection of fixed window and variable window's width to achieve the window's width automatic adjustment value between the different estimation points based on the sample distribution. Then the probability density curve using kernel density estimation algorithm as radar emitter signal parameters characteristics stored into database.

The Method of Optimal Group Based on the Kernel Density Estimation and the Close Degree

2014 ◽  
Vol 989-994 ◽  
pp. 3689-3692
Author(s):  
Fei Ye ◽  
Xin Wang ◽  
Dong Hui Peng ◽  
Chuan Hai Jiao
Keyword(s):  
Probability Density Function ◽  
Probability Density ◽  
Density Estimation ◽  
Kernel Density Estimation ◽  
Kernel Density ◽  
Estimation Algorithm ◽  
Parameter Analysis ◽  
Sample Distribution ◽  
Group Number ◽  
Selection Of

The optimal group is an important problem of histogram algorithm, and how to confirm group number has not a quantitative rule. So the concept of the close degree is imported to make the close degree between the upper contour line of histogram and the PDF(probability density function) of parameter as the judging criteria of optimal group. With the unknown of the PDF of parameter, the improved kernel density estimation algorithm can pre-select and estimate the PDF. This improved kernel density estimation algorithm combine the selection of fixed window and variable window's width to achieve the window's width automatic adjustment value between the different estimation points based on the sample distribution. In the parameter analysis of radar emitter signal, the algorithm based on improved kernel density estimation and close degree is used to determine optimal group, and the result indicate that this method is effective and can search the optimal group automatically.

scholarly journals Author Correction: An extended Weight Kernel Density Estimation model forecasts COVID-19 onset risk and identifies spatiotemporal variations of lockdown effects in China

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Wenzhong Shi ◽  
Chengzhuo Tong ◽  
Anshu Zhang ◽  
Bin Wang ◽  
Zhicheng Shi ◽  
...  
Keyword(s):  
Density Estimation ◽  
Kernel Density Estimation ◽  
Kernel Density ◽  
Spatiotemporal Variations ◽  
Estimation Model

A Correction to this paper has been published: https://doi.org/10.1038/s42003-021-01924-6

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