Efficient anisotropic quasi-Pwavefield extrapolation using an isotropic low-rank approximation
نویسندگان
چکیده
منابع مشابه
An Efficient, Sparsity-Preserving, Online Algorithm for Low-Rank Approximation
Low-rank matrix approximation is a fundamental tool in data analysis for processing large datasets, reducing noise, and finding important signals. In this work, we present a novel truncated LU factorization called Spectrum-Revealing LU (SRLU) for effective low-rank matrix approximation, and develop a fast algorithm to compute an SRLU factorization. We provide both matrix and singular value appr...
متن کاملLow-rank Tensor Approximation
Approximating a tensor by another of lower rank is in general an ill posed problem. Yet, this kind of approximation is mandatory in the presence of measurement errors or noise. We show how tools recently developed in compressed sensing can be used to solve this problem. More precisely, a minimal angle between the columns of loading matrices allows to restore both existence and uniqueness of the...
متن کاملStructured Low Rank Approximation
Abstract. This paper concerns the construction of a structured low rank matrix that is nearest to a given matrix. The notion of structured low rank approximation arises in various applications, ranging from signal enhancement to protein folding to computer algebra, where the empirical data collected in a matrix do not maintain either the specified structure or the desirable rank as is expected ...
متن کاملDynamical low-rank approximation
In low-rank approximation, separation of variables is used to reduce the amount of data in computations with high-dimensional functions. Such techniques have proved their value, e.g., in quantum mechanics and recommendation algorithms. It is also possible to fold a low-dimensional grid into a high-dimensional object, and use low-rank techniques to compress the data. Here, we consider low-rank t...
متن کاملDynamical Low-Rank Approximation
For the low rank approximation of time-dependent data matrices and of solutions to matrix differential equations, an increment-based computational approach is proposed and analyzed. In this method, the derivative is projected onto the tangent space of the manifold of rank-r matrices at the current approximation. With an appropriate decomposition of rank-r matrices and their tangent matrices, th...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Geophysical Journal International
سال: 2017
ISSN: 0956-540X,1365-246X
DOI: 10.1093/gji/ggx543