Compressive spectral renormalization method
Yükleniyor...
Dosyalar
Tarih
2018-09-09
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Işık University Press
Erişim Hakkı
info:eu-repo/semantics/openAccess
Attribution-NonCommercial-NoDerivs 3.0 United States
Attribution-NonCommercial-NoDerivs 3.0 United States
Özet
In this paper a novel numerical scheme for finding the sparse self-localized states of a nonlinear system of equations with missing spectral data is introduced. As in the Petviashivili's and the spectral renormalization method, the governing equation is transformed into Fourier domain, but the iterations are performed for far fewer number of spectral components (M) than classical versions of the these methods with higher number of spectral components (N). After the converge criteria is achieved for M components, N component signal is reconstructed from M components by using the l(1) minimization technique of the compressive sampling. This method can be named as compressive spectral renormalization (CSRM) method. The main advantage of the CSRM is that, it is capable of finding the sparse self-localized states of the evolution equation(s) with many spectral data missing.
Açıklama
Anahtar Kelimeler
Spectral renormalization, Petviashivili's method, Compressive sampling, Spectral methods, Nonlinear Schrodinger equation, Waves, Solitons
Kaynak
TWMS Journal of Applied and Engineering Mathematics
WoS Q Değeri
N/A
Scopus Q Değeri
Q4
Cilt
8
Sayı
2
Künye
Bayındır, C. (2018). Compressive spectral renormalization method. TWMS Journal of Applied and Engineering Mathematics, 8(2), 425-437.
