منابع مشابه
Migration Deconvolution versus Least Squares Migration
Both migration deconvolution (MD) and least squares migration (LSM) are capable of improving the resolution and suppress acquisition footprints in migrated images. In this report, I investigate the relative performance of these two methods in enhancing migration image quality, suppressing artifacts and computational efficiency. Both MD and LSM were implemented on synthetic data generated from p...
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Both migration deconvolution (MD) and least squares migration (LSM) are capable of improving the resolution and suppress acquisition footprints in migrated images. In this paper, we investigate the relative performance of these two technologies in enhancing migration image quality, suppressing artifacts and computational efficiency. Both MD and LSM were tested on SEG/EAGE overthrust models. The...
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We consider regularized least-squares (RLS) with a Gaussian kernel. We prove that if we let the Gaussian bandwidth σ → ∞ while letting the regularization parameter λ→ 0, the RLS solution tends to a polynomial whose order is controlled by the rielative rates of decay of 1 σ2 and λ: if λ = σ−(2k+1), then, as σ →∞, the RLS solution tends to the kth order polynomial with minimal empirical error. We...
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Recursive estimates of large systems of equations in the context of least squares fitting is a common practice in different fields of study. For example, recursive adaptive filtering is extensively used in signal processing and control applications. The necessity of solving least squares problem via recursive algorithms comes from the need of fast real-time signal processing strategies. Computa...
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ژورنال
عنوان ژورنال: Journal of Geophysics and Engineering
سال: 2017
ISSN: 1742-2132,1742-2140
DOI: 10.1088/1742-2140/14/1/184