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ICPR
2008
IEEE
14 years 8 months ago
Kernel bandwidth estimation in methods based on probability density function modelling
In kernel density estimation methods, an approximation of the data probability density function is achieved by locating a kernel function at each data location. The smoothness of ...
Adrian G. Bors, Nikolaos Nasios
ICANN
2009
Springer
14 years 1 days ago
Bayesian Estimation of Kernel Bandwidth for Nonparametric Modelling
Kernel density estimation (KDE) has been used in many computational intelligence and computer vision applications. In this paper we propose a Bayesian estimation method for findin...
Adrian G. Bors, Nikolaos Nasios
CSDA
2004
188views more  CSDA 2004»
13 years 7 months ago
A bandwidth selection for kernel density estimation of functions of random variables
In this investigation, the problem of estimating the probability density function of a function of m independent identically distributed random variables, g(X1, X2, ..., Xm) is co...
A. R. Mugdadi, Ibrahim A. Ahmad
IJCNN
2007
IEEE
14 years 1 months ago
Probability Density Function Estimation Using Orthogonal Forward Regression
— Using the classical Parzen window estimate as the target function, the kernel density estimation is formulated as a regression problem and the orthogonal forward regression tec...
Sheng Chen, Xia Hong, Chris J. Harris
TSMC
2010
13 years 2 months ago
Probability Density Estimation With Tunable Kernels Using Orthogonal Forward Regression
A generalized or tunable-kernel model is proposed for probability density function estimation based on an orthogonal forward regression procedure. Each stage of the density estimat...
Sheng Chen, Xia Hong, Chris J. Harris