Article
Engineering, Electrical & Electronic
Lin Geng, Ling-Zhi Zhou, Hao Shen, Chun-Dong He, Feng Xie
Summary: An improved iterative reweighted least-squares algorithm is proposed to reconstruct the transient acoustic field based on the real-time near-field acoustic hologram method. The algorithm promotes the sparsity of the solution by controlling the weighting matrix. Numerical simulations and experiments demonstrate the effectiveness and superiority of the proposed method in reconstructing the transient acoustic field.
Article
Computer Science, Software Engineering
Damian Straszak, Nisheeth K. Vishnoi
Summary: This paper explores the connection between the IRLS algorithm and slime mold dynamics, showing that they can be related through a new dynamical system - the Meta-Algorithm. Convergence and complexity bounds for the Meta-Algorithm are proven, providing new possibilities for solving the undirected transshipment problem.
MATHEMATICAL PROGRAMMING
(2022)
Article
Engineering, Multidisciplinary
Chenghua Zhang, Zhangyan Zhao, Yang Liu
Summary: This study proposes an advanced iteratively weighted least squares solution based on the weighted least squares to estimate the transformation parameters for measurement datum transformation. Simulation experiments and verification show that the proposed algorithm can effectively reduce the influence of gross errors to obtain reliable measurement datum transformation parameters.
MEASUREMENT SCIENCE AND TECHNOLOGY
(2023)
Article
Engineering, Aerospace
Weiwei Wang, Zhangjian Lu, Ye Tian, Lang Bian, Guoyong Wang, Lixin Zhang
Summary: This paper introduces the research on the application of Doppler-aided positioning method in fused LEO navigation systems, which can improve the positioning performance and availability, and expand its application scenarios.
Article
Computer Science, Information Systems
Xiao He, Ye Li, Jian Tan, Bin Wu, Feifei Li
Summary: Seasonal-trend decomposition is a fundamental concept in time series analysis, but existing methods are not efficient for real-time analysis. In this paper, we propose OneShotSTL, an algorithm that can decompose time series online with high efficiency and accuracy. OneShotSTL is more than 1,000 times faster than batch methods and achieves comparable or even better accuracy. Experimental results on benchmark datasets demonstrate its superiority.
PROCEEDINGS OF THE VLDB ENDOWMENT
(2023)
Article
Computer Science, Artificial Intelligence
Hongwei Dong, Liming Yang
Summary: A novel kernel-based regression method with better noise robustness is proposed in this paper, utilizing the l(s)-loss function instead of the traditional l(2)-loss. The theoretical verification and experimental results confirm the good performance of this method.
KNOWLEDGE AND INFORMATION SYSTEMS
(2021)
Article
Statistics & Probability
Peng Zhang, Ben Liu, Jingjing Pan
Summary: An iteratively reweighted least squares (IRLS) method is proposed for estimating polyserial and polychoric correlation coefficients. The method fits weighted linear regression models using conditional expected values and obtains the estimators' standard errors through data summaries. Compared to traditional methods, this approach is faster and has advantages in computing speed.
JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS
(2023)
Article
Mathematics, Applied
Yun Cai, Ying Wang
Summary: This paper provides convergence, convergence rate, and stability analysis of the BIRLS algorithm for block sparse recovery in the presence of noise. The convergence and stability of BIRLS are proved, and the convergence rate is characterized.
LINEAR ALGEBRA AND ITS APPLICATIONS
(2021)
Article
Automation & Control Systems
Clement Chahbazian, Karim Dahia, Nicolas Merlinge, Benedicte Winter-Bonnet, Aurelien Blanc, Christian Musso
Summary: The paper derives a recursive formula of the Fisher information matrix on Lie groups and applies it to nonlinear Gaussian systems on Lie groups for testing. The proposed recursive CRLB is consistent with state-of-the-art filters and exhibits representative behavior in estimation errors. This paper provides a simple method to recursively compute the minimal variance of an estimator on matrix Lie groups, which is fundamental for implementing robust algorithms.
Article
Engineering, Electrical & Electronic
Michael Fauss, Alex Dytso, H. Vincent Poor
Summary: Both the classic and Bayesian Cramer-Rao bounds can be obtained by minimizing the mean square error of an estimator while constraining the underlying distribution to be within a Fisher information ball. The results allow for nonstandard interpretations of the Cramer-Rao bound and provide a template for novel bounds on the accuracy of estimators.
Article
Energy & Fuels
Prarthana Pillai, Sneha Sundaresan, Krishna R. Pattipati, Balakumar Balasingam
Summary: Battery management systems are crucial for the safety and reliability of battery packs. This paper presents an approach to estimate the internal equivalent circuit model parameters of a battery separately, without requiring knowledge of the battery's state of charge.
Article
Spectroscopy
Anatoly A. Saveliev, Ekaterina V. Galeeva, Dmitry A. Semanov, Roman R. Galeev, Ilshat R. Aryslanov, Tatyana S. Falaleeva, Rustam R. Davletshin
Summary: A novel adaptive noise model based on iteratively reweighted penalized least squares (ANM-IRPLS) method is proposed for Raman spectrum baseline correction, offering better results in background removal compared to existing methods.
JOURNAL OF RAMAN SPECTROSCOPY
(2022)
Article
Engineering, Electrical & Electronic
Swagata Nandi, Debasis Kundu
Summary: This paper investigates the problem of estimating parameters in a multichannel sinusoidal model. Two estimation methods, the minimization of the sum of residual sum of squares and the use of more efficient generalized least squares estimators, are proposed and compared through simulation experiments. The results show that the variances of the generalized least squares estimators reach the Cramer-Rao lower bound, and the computational complexity does not significantly increase with the number of channels.
CIRCUITS SYSTEMS AND SIGNAL PROCESSING
(2022)
Article
Engineering, Electrical & Electronic
Antonio Alberto D'Amico, Michele Morelli, Marco Moretti
Summary: This study investigates the estimation of sinusoidal frequency in the presence of white Gaussian noise, focusing on DFT interpolation methods and optimization. Evaluating the CRB and maximum likelihood DFT interpolator helps assess the accuracy and applicability of the methods. This is important for improving estimation accuracy and reducing computational burden.
IEEE TRANSACTIONS ON COMMUNICATIONS
(2022)
Article
Chemistry, Analytical
Yuchen Fan, Zhenqi Shi, Shengli Ma, Sayyeda Zeenat Anwer Razvi, Yige Fu, Tao Chen, Jason Gruenhagen, Kelly Zhang
Summary: In this study, a modeling approach based on UV spectra was developed to quantify the loading of nucleic acid cargos in LNPs in-situ. The method showed similar predictive performance as more complicated experimental approaches and significantly saved analytical time and efforts.
ANALYTICAL CHEMISTRY
(2022)
