Reproducing Kernel Hilbert Space and Coalescence Hidden-variable Fractal Interpolation Functions

• Autorzy: Prasad Srijanani Anurag

Identyfikatory

DOI

10.1515/dema-2019-0027

• Języki publikacji: EN

Abstrakty

EN

Reproducing Kernel Hilbert Spaces (RKHS) and their kernel are important tools which have been found to be incredibly useful in many areas like machine learning, complex analysis, probability theory, group representation theory and the theory of integral operator. In the present paper, the space of Coalescence Hidden-variable Fractal Interpolation Functions (CHFIFs) is demonstrated to be an RKHS and its associated kernel is derived. This extends the possibility of using this new kernel function, which is partly self-affine and partly non-self-affine, in diverse fields wherein the structure is not always self-affine.

Słowa kluczowe

EN

fractal; interpolation; coalescence; attractor; reproducing kernel; Hilbert space

PL

fraktal; interpolacja; koalescencja; atraktor; jądro reprodukujące; przestrzeń Hilberta

• Wydawca: De Gruyter
• Czasopismo: Demonstratio Mathematica
• Rocznik: 2019
• Tom: Vol. 52, nr 1
• Strony: 467--474
• Opis fizyczny: Bibliogr. 21 poz.

Twórcy

autor

Prasad Srijanani Anurag

• Department of Mathematics, Indian Institute of Technology Tirupati, India

Bibliografia

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Uwagi

PL

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).