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Nonlinear Signal Processing Based on Reproducing Kernel Hilbert Space

Nonlinear Signal Processing Based on Reproducing Kernel Hilbert Space

 

Marketed By :  LAP LAMBERT Academic Publishing   Sold By :  Kamal Books International  
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  • Product Description
 

Over the last few decades, there has been much research on reproducing kernel Hilbert space (RKHS) for machine learning. This monograph applies RKHS for nonlinear signal processing. It proposes a new statistical descriptor, called correntropy, to characterize the higher order statistical information and nonlinearity intrinsic to random processes. Correntropy and centered correntropy functions can be formulated as "generalized" correlation and covariance functions on nonlinearly transformed random signals via the data independent kernel functions. Those nonlinearly transformed signals appear on the sphere in the reproducing kernel Hilbert space induced by the kernel functions if isotropic kernel functions are used. The book offers new insights into the application of RKHS in nonlinear signal processing. Graduate students, professionals and researchers who are working on nonlinear signal processing and machine learning will find insightful information from the book.

Product Specifications
SKU :COC32126
Country of ManufactureIndia
Product BrandLAP LAMBERT Academic Publishing
Product Packaging InfoBox
In The Box1 Piece
Product First Available On ClickOnCare.com2015-07-29
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