Title :
Density estimation using kernel method with distorter
Author :
Tanaka, Hiroshi ; Miyoshi, Tetsuya ; Ichihashi, Hidetomo
Author_Institution :
Osaka Prefectural Univ., Sakai, Japan
Abstract :
We propose a method to determine the bandwidth of a kernel function when the probability density function is to be estimated by the kernel method. A new criterion to evaluate the bandwidth is presented, which represents the difference between the estimated density function using the observations and the one using the transformed observations by a nonlinear function called “distorter”
Keywords :
feedforward neural nets; nonparametric statistics; probability; state estimation; transfer functions; bandwidth; density estimation; distorter; kernel method; nonlinear function; probability density function; Bandwidth; Density functional theory; Educational institutions; Industrial engineering; Kernel; Neural networks; Nonlinear distortion; Phase locked loops; Probability density function; Radial basis function networks;
Conference_Titel :
Neural Networks Proceedings, 1998. IEEE World Congress on Computational Intelligence. The 1998 IEEE International Joint Conference on
Conference_Location :
Anchorage, AK
Print_ISBN :
0-7803-4859-1
DOI :
10.1109/IJCNN.1998.685948