Search Results - least square iterative linear inversion algorithm*

A Concrete Core Void Imaging Approach and Parameter Analysis of Concrete-Filled Steel Tube Members Using Travel Time Tomography: Multi-Physics Simulations and Experimental Studies by Zheng, Wenting, Xu, Bin, Xia, Zongjun, Wang, Jiang, Liu, Jingliang, Yao, Yudi, Wang, Yifei

“…) with a least square iterative linear inversion algorithm is first introduced to quantitatively identify and visualize…”
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Prestack AVA inversion of exact Zoeppritz equations based on modified Trivariate Cauchy distribution by Zhou, Lin, Li, Jingye, Chen, Xiaohong, Liu, Xingye, Chen, Li

“… However, conventional prestack amplitude variation with incidence angle inversion method is strongly influenced by the accuracy of the approximate Zoeppritz equations, which suppresses weak…”
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Prestack amplitude versus angle inversion for Young's modulus and Poisson's ratio based on the exact Zoeppritz equations by Zhou, Lin, Li, Jingye, Chen, Xiaohong, Liu, Xingye, Chen, Li

“… Conventionally, they are indirectly calculated by the rock physics method or estimated by approximate formula inversion…”
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Iterative image-domain decomposition for dual-energy CT by Niu, Tianye, Dong, Xue, Petrongolo, Michael, Zhu, Lei

“…: The proposed algorithm is formulated in the form of least-square estimation…”
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Distributed iterative reweighted least squares algorithm for high-resolution finite-frequency traveltime velocity inversion using VSP data by Zhang, Houzhu, Liang, Hong, Liu, Hongwei, Zhang, Shuo

“… We analyze the characteristics of FFTVI from the computational point of view. A parallel version, Iterative Reweighted Least Squares (IRLS…”
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An Inversion of NMR Echo Data Based on a Normalized Iterative Hard Thresholding Algorithm by Guo, Jiangfeng, Xie, Ranhong

“… In this letter, a surrogate objective function of an NMR inversion without an explicit regularization term based on least-squares fitting is introduced to avoid the process of choosing…”
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A unified preconditioned minimal residual (PMR) algorithm for matrix problems: Linear systems, multiple right-hand sides linear systems, least squares problems, inversion and pseudo-inversion with application to color image encryption by Shirilord, Akbar, Dehghan, Mehdi

“…In this article, we introduce a preconditioned minimal residual (PMR) algorithm designed to address a wide range of matrix equations and linear systems…”
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A New Vector Waveform Inversion Algorithm for Simultaneous Updating of Conductivity and Permittivity Parameters From Combination Crosshole/Borehole-to-Surface GPR Data by Meles, Giovanni Angelo, Van der Kruk, Jan, Greenhalgh, Stewart A, Ernst, Jacques R, Maurer, Hansruedi, Green, Alan G

“… The inversion is formulated as a nonlinear least squares problem in which the misfit between observed and modeled data is minimized…”
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Transient Electromagnetic Inversion Based on Improved Supervised Descent Method by Wu, Xinyu, Zhang, Yingying, Xie, Bin, Wu, Wenyu

“…Supervised descent method (SDM) is a machine learning method mainly used to solve the least squares problem, which is divided into a training phase and a prediction phase…”
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A Fast Sparse Azimuth Super-Resolution Imaging Method of Real Aperture Radar Based on Iterative Reweighted Least Squares With Linear Sketching by Tuo, Xingyu, Zhang, Yin, Huang, Yulin, Yang, Jianyu

“…> norm minimization problem mathematically. Iterative reweighted algorithm can effectively solve the <inline-formula><tex-math notation="LaTeX">L_1</tex-math></inline-formula…”
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Randomized Gauss–Seidel iterative algorithms for Extreme Learning Machines by Subramani, Chinnamuthu, Jagannath, Ravi Prasad K., Kuppili, Venkatanareshbabu

“… ELM training requires solving a system of linear equations, where solution accuracy directly impacts model performance…”
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Wavelet-based 3-D inversion for frequency-domain airborne EM data by Liu, Yunhe, Farquharson, Colin G, Yin, Changchun, Baranwal, Vikas C

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Low-complexity signal detection for large-scale MIMO systems with second-order Richardson method by Khoso, Imran A, Zhang, Xiaofei, Shaikh, Abdul Hayee

“…Linear minimum mean-square error (MMSE) detection achieves near-optimal performance in large-scale multiple-input multiple-output (LS-MIMO…”
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A comparison of direct and iterative finite element inversion techniques in dynamic elastography by Honarvar, M, Rohling, R, Salcudean, S E

“… This problem has been solved with both direct and iterative FEM schemes. Each of these methods has its own advantages and disadvantages which are examined in this paper…”
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An Iterative Discrete Least Square Estimator with Dynamic Parameterization via Deep-Unfolding by Ando, Kengo, Iimori, Hiroki, Rou, Hyeon Seok, Freitas de Abreu, Giuseppe Thadeu, G, David Gonzalez, Gonsa, Osvaldo

“…We propose a new dynamic parameterization approach via deep unfolding as an extension of the recently-introduced iterative discrete least square (IDLS…”
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Greedy search method for separable nonlinear models using stage Aitken gradient descent and least squares algorithms by Chen, Jing, Mao, Yawen, Gan, Min, Wang, Dongqing, Zhu, Quanmin

“… The linear parameters are estimated using the least squares algorithm, and the nonlinear parameters are updated based on the AGD algorithm…”
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A homotopy continuation inversion of geoelectrical sounding data by Ghanati, Reza, Müller-Petke, Mike

“… constraints on the physical properties. To mitigate this problem, we present a globally convergent Homotopy continuation algorithm to solve the nonlinear least squares problem through a path-tracking strategy in model space…”
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Full waveform inversion by proximal Newton method using adaptive regularization by Aghamiry, H S, Gholami, A, Operto, S

“… In this paper, we propose two generic optimization algorithms to implement arbitrary regularization in non-linear inverse problems such as full-waveform inversion (FWI…”
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Iterative Pseudo-Sparse Partial Least Square and its Higher-Order variant: Application to inference from high-dimensional biosignals by Einizade, Aref, Sardouie, Sepideh Hajipour

“…Partial Least Square (PLS) regression and its (L1 or L2 norm) regularized versions have been proposed to handle the high-dimensionality aspects of the problem at hand and select relevant features…”
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Fast Sampling and Reconstruction for Linear Inverse Problems: From Vectors to Tensors by Wang, Fen, Cheung, Gene, Li, Taihao, Du, Ying, Ruan, Yu-Ping

“… In practice, a target signal is commonly assumed to be linear in the residing factor mode(s) with low-dimensional parameters, and thus can be recovered from partial samples by solving a linear inverse problem (LIP…”
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