Results 31 to 40 of about 91,180 (283)
The Consequences of Non-Normality [PDF]
, 2001 The non-normality of Wilson-type lattice Dirac operators has important consequences - the application of the usual concepts from the textbook (hermitian) quantum mechanics should be reconsidered. This includes an appropriate definition of observables and
Hip, I +4 more
core +2 more sources
Sensors, 2023 Addressing insufficient and irregular sampling is a difficult challenge in seismic processing and imaging. Recently, rank reduction methods have become popular in seismic processing algorithms for simultaneous denoising and interpolating.
Farzaneh Bayati, Daniel Trad
doaj +1 more source
Perturbation expansions and error bounds for the truncated singular value decomposition [PDF]
Linear Algebra and its Applications, 2021 Accepted to Linear Algebra and Its ...
Trung Vu +2 more
openaire +3 more sources
Compressed Passive Macromodeling [PDF]
, 2012 This paper presents an approach for the extraction of passive macromodels of large-scale interconnects from their frequency-domain scattering responses. Here, large scale is intended both in terms of number of electrical ports and required dynamic model ...
Grivet-Talocia, S. +1 more
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Truncated singular value decomposition for through‐the‐wall microwave imaging application [PDF]
IET Microwaves, Antennas & Propagation, 2020 We considered differential through‐the‐wall microwave imaging with different formulations of truncated singular value decomposition (TSVD) method with a non‐anechoic experiment. Previous studies employ TSVD with single transmitting/measuring antenna, while we show how to apply the TSVD in case of a moving linear transmitting/measuring antenna array ...
Semih Doğu +3 more
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, 2018 In this paper, we propose new randomization based algorithms for large scale linear discrete ill-posed problems with general-form regularization: ${\min} \|Lx\|$ subject to ${\min} \|Ax - b\|$, where $L$ is a regularization matrix.
Jia, Zhongxiao, Yang, Yanfei
core +1 more source
Fractional Norm Regularization Using Truncated Singular Value Decomposition
IEEE AccessIn a previous work, a solution to the fractional norm regularization (FNR) was discovered in a closed form and an inverse perturbation was adopted as a tool to overcome the ill condition of a matrix whose inverse is required by the fixed-point FNR.
Bamrung Tausiesakul +1 more
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An Out of Memory tSVD for Big-Data Factorization
IEEE Access, 2020 Singular value decomposition (SVD) is a matrix factorization method widely used for dimension reduction, data analytics, information retrieval, and unsupervised learning.
Hector Carrillo-Cabada +4 more
doaj +1 more source
Conformal phased array with beam forming for airborne satellite communication [PDF]
, 2008 For enhanced communication on board of aircraft novel antenna systems with broadband satellite-based capabilities are required. The installation of such systems on board of aircraft requires the development of a very low-profile aircraft antenna, which ...
Heideman, R.G. +8 more
core +2 more sources
Image Denoising Using Hybrid Singular Value Thresholding Operators
IEEE Access, 2020 Truncated singular value decomposition (TSVD) is a simple and efficient technique for patch-based image denoising, in which a hard thresholding operator is utilized to set some small singular values to zero.
Fan Zhang +3 more
doaj +1 more source