Kernel smoothing has greatly evolved since its inception to become an essential methodology in the Data Science tool kit for the 21st century. Its widespread adoption is due to its fundamental role for multivariate exploratory data analysis, as well...Lasīt vairāk
This book is an essentially self-contained presentation of the theory of reproducing kernels in connection with integral transforms in the framework of Hilbert spaces. It presents a variety of concrete results of integral transforms application for...Lasīt vairāk
This volume considers the kernel functions for higher-order systems, contains a detailed discussion of the envelope method for the locating of singularities of elliptic equations, and reviews of some new results in Clifford analysis....Lasīt vairāk
Describes and discusses the variants of kernel analysis methods for data types that have been intensely studied in recent years This book covers kernel analysis topics ranging from the fundamental theory of kernel functions to its applications....Lasīt vairāk
(Izdošanas datums: 23-Oct-2009, Izdevniecība: John Wiley & Sons Inc, ISBN-13: 9780470748992)
Editors and contributors are experts in the field of kernel methods (KMs) for remote sensing. Provides state of the art knowledge, analysing the methodological and practical challenges related to the application of KMs to remote sensing problems....Lasīt vairāk
(Izdošanas datums: 15-Oct-2007, Izdevniecība: Imperial College Press, ISBN-13: 9781860949715)
The k(GV) problem has been finally solved, completing the work of a series of authors. This book describes the developments, ideas and methods, leading to this result....Lasīt vairāk
Kernel smoothing refers to a general methodology for recovery of underlying structure in data sets. Nonparametric regression and density estimation are two of the most fundamental problems to which kernel smoothing provides a simple and effective so...Lasīt vairāk
