Literaturdeki iki kor zaman-siklik kaynak ayristirma yontemi astrofiziksel gorunntiu karisimlarina uyarlanarak dort algoritma gelistirilmis ve bu karisimlarin kozmik bilesenlerine ayristirilmasinda kullanilmistir. Bu gorunntuler; fiziksel modellerine uygun olarak benzetilmi, olan kozmik mikrodalga arkaplan (KMA) isinimi, galaktik toz ve senkrotron bilesenleri gercekci katsayilar ile karistirilarak ve gercekci gurultu duzeylerinde benzetilmis duragan olmayan gurultu bilesenleri eklenilmek suretiyle bilgisayarda benzetilmistir. Gelistirilen algoritmalarin performanslari FastICA (hizli bagimsiz bilesenler analizi) algoritmasi ile karsilastirilmis ve, KMA-senkrotron karisimlarindan KMA bileseninin 3.16 desibele varan oranlarda bir iyilestirme ile elde edildigi gorulmustur.
Two blind time-frequency source separation methods in the literature are adapted to astrophysical image mixtures and four algorithms are developed to separate them into their cosmic components; cosmic microwave background (CMB) radiation, galactic dust and synchrotron. These components simulated according to their physical models are mixed via realistic coefficients, and are subjected to simulated additive, nonstationary Gaussian noise components of realistic power levels, to yield image mixtures. The developed algorithms are compared with the FastICA algorithm and CMB component is found to be recovered with an improvement reaching to 3.16 decibels from CMB-synchrotron mixtures.
Gürültülü Astrofiziksel Görüntü Karışımlarının Kör Zaman-Sıklık Kaynak Ayrıştırma Yöntemleri ile Ayrıştırılmas = Separation of noisy astrophysical images by blind time-frequency source
Kuruoglu E E;
2007
Abstract
Two blind time-frequency source separation methods in the literature are adapted to astrophysical image mixtures and four algorithms are developed to separate them into their cosmic components; cosmic microwave background (CMB) radiation, galactic dust and synchrotron. These components simulated according to their physical models are mixed via realistic coefficients, and are subjected to simulated additive, nonstationary Gaussian noise components of realistic power levels, to yield image mixtures. The developed algorithms are compared with the FastICA algorithm and CMB component is found to be recovered with an improvement reaching to 3.16 decibels from CMB-synchrotron mixtures.| File | Dimensione | Formato | |
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