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Some Regularity Theorems on Kernel Methods of Summation for Functions of a Complex Variable.
We develop a different technique based on kernel phase shifts which we have found to show substantially better results.
Therefore, we have developed a new tool, called Notos, to identify DNA methylation signatures within CpGo/e ratios based on kernel density estimations36.
This paper presents a new approach based on kernel functions to solve activity prediction problem for chemical compounds.
In this paper, a new nonlinear process monitoring technique based on kernel principal component analysis (KPCA) is developed.
A clustering technique based on kernel density estimation is described that identifies clusters in terms of the design variables.
Several functions are constructed for evaluating the significance of features based on kernel approximation and fuzzy entropy.
A new monitoring method based on kernel entropy component analysis KECA) is proposed for nonlinear chemical process.
In this paper, a new statistical method, based on kernel density estimation, is used for analyzing fractal coding parameters.
Nearest local maximum searching algorithm (NLMSA), an unsupervised clustering algorithm based on kernel density estimation, is proposed.
In this context, this article presents a methodology to directly reconstruct this functional based on kernel density estimators.
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CEO of Professional Science Editing for Scientists @ prosciediting.com