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ICPR
2008
IEEE
14 years 5 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
13 years 9 months 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 4 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
13 years 11 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
12 years 11 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