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IEEE Transactions on Image Processing, ISSN 1057-7149, 02/2007, Volume 16, Issue 2, pp. 463 - 478
This paper describes new extensions to the previously published multivariate alteration detection (MAD) method for change detection in bi-temporal, multi- and... 
Hyperspectral sensors | Boosting | Time measurement | MAD transformation | Calibration | Data mining | Remote sensing | iteratively reweighted multivariate alteration detection (IR-MAD) | Gain measurement | Iterative methods | Autocorrelation | regularization or penalization | Canonical correlation analysis (CCA) | Hyperspectral imaging | MAD transformation Regularization or penalization | Iteratively reweighted multivariate alteration detection (IR-MAD) | REGRESSION | IMAGERY | UNSUPERVISED CHANGE DETECTION | remote sensing | PRINCIPAL COMPONENTS | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | ENGINEERING, ELECTRICAL & ELECTRONIC | SETS | canonical correlation analysis (CCA) | VARIABLES | Multivariate Analysis | User-Computer Interface | Information Storage and Retrieval - methods | Artificial Intelligence | Image Interpretation, Computer-Assisted - methods | Models, Statistical | Subtraction Technique | Computer Graphics | Algorithms | Numerical Analysis, Computer-Assisted | Computer Simulation | Signal Processing, Computer-Assisted | Image Enhancement - methods | Cluster Analysis | Usage | Image processing | Analysis | Correlation (Statistics) | Research | Multivariate analysis | Methods | Studies | Correlation analysis | Change detection | Mathematical analysis | Rural areas | Transformations | Regularization | Invariants
Journal Article
Mathematical Methods in the Applied Sciences, ISSN 0170-4214, 09/2018, Volume 41, Issue 14, pp. 5481 - 5492
We consider the problem of compressed sensing with a coherent tight frame and design an iteratively reweighted least squares algorithm to solve it. To analyze... 
tight frame | compressed sensing | iteratively reweighted method | sufficient D‐NSP | D‐RIP | sufficient D-NSP | D-RIP | MATHEMATICS, APPLIED | SPARSE REPRESENTATION | UNCERTAINTY PRINCIPLE | MINIMIZATION | Analysis | Algorithms | Wavelet | Fourier transforms | Discrete cosine transform
Journal Article
IEEE Transactions on Instrumentation and Measurement, ISSN 0018-9456, 8/2019, pp. 1 - 1
Regularization method has been utilized to address the ill-posed inverse problem of electrical resistance tomography (ERT). As one of the regularization... 
weighting matrix | total variation regularization | iteratively reweighted least squares method | scaling factor | Electrical resistance tomography
Journal Article
2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ISSN 1520-6149, 03/2008, pp. 3869 - 3872
Conference Proceeding
Journal of Sound and Vibration, ISSN 0022-460X, 10/2019, Volume 458, pp. 376 - 388
Journal Article
Applied Mathematics and Computation, ISSN 0096-3003, 01/2020, Volume 364, p. 124678
We propose a method, called ACQUIRE, for the solution of constrained optimization problems modeling the restoration of images corrupted by Poisson noise. The... 
Iteratively reweighted norm approach | Quadratic approximation | Image restoration | Poisson noise | TV regularization | MATHEMATICS, APPLIED | GRADIENT METHODS | RECONSTRUCTION | QUADRATIC-PROGRAMMING PROBLEMS | ALGORITHMS | PROJECTION | DECONVOLUTION | TOTAL VARIATION MINIMIZATION
Journal Article
IEEE Transactions on Signal Processing, ISSN 1053-587X, 01/2019, Volume 67, Issue 2, pp. 490 - 503
Journal Article
IEEE Geoscience and Remote Sensing Letters, ISSN 1545-598X, 12/2019, pp. 1 - 5
Sparse representation (SR)-based denoising method attenuates random seismic noise trace-by-trace, which may not be able to employ the coherency between... 
random noise attenuation | common offset gather (COG) | multiple measurement vectors (MMVs) | iteratively reweighted (IR) | 1 norm regularization | ℓ2 | Alternating direction method of multipliers (ADMM)
Journal Article
by Yu, PR and Pong, TK
COMPUTATIONAL OPTIMIZATION AND APPLICATIONS, ISSN 0926-6003, 06/2019, Volume 73, Issue 2, pp. 353 - 386
Iteratively reweighted 1 algorithm is a popular algorithm for solving a large class of optimization problems whose objective is the sum of a Lipschitz... 
Extrapolation | MATHEMATICS, APPLIED | Kurdyka-ojasiewicz property | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | Iteratively reweighted l algorithm | Algorithms
Journal Article
Journal of Computational and Applied Mathematics, ISSN 0377-0427, 03/2018, Volume 331, pp. 64 - 81
In this paper, we establish a non-convex Lp norm relaxation model for low Tucker rank tensor recovery problem, and equivalently transform it to a non-convex... 
Tensor completion | [formula omitted] norm | Alternative direction method of multipliers | Iteratively reweighted algorithms | Low Tucker rank tensor recovery | norm | MATHEMATICS, APPLIED | CONVERGENCE | L-p norm | Analysis | Algorithms
Journal Article
SIAM Journal on Optimization, ISSN 1052-6234, 2011, Volume 21, Issue 4, pp. 1614 - 1640
We present and analyze an efficient implementation of an iteratively reweighted least squares algorithm for recovering a matrix from a small number of linear... 
Iteratively reweighted least squares | Low-rank matrix recovery | Matrix completion | low-rank matrix recovery | MATHEMATICS, APPLIED | matrix completion | iteratively reweighted least squares | EQUATIONS | VALUES | COMPLETION
Journal Article
Infrared Physics and Technology, ISSN 1350-4495, 03/2016, Volume 75, pp. 107 - 116
•The iteratively reweighted algorithm is used to optimize the UTV correction model.•Derive a formula to automatically update the regularization parameter.•The... 
Unidirectional variational | Iteratively reweighted least square (IRLS) | Estimate regularization parameters | Non-uniformity correction | INSTRUMENTS & INSTRUMENTATION | PHYSICS, APPLIED | REMOVAL | MINIMIZATION | FOCAL-PLANE ARRAY | NOISE | OPTICS | MODIS | Analysis | Models | Algorithms | Infrared | Noise | Least squares method | Adaptive algorithms | Images | Mathematical models | Nonuniformity
Journal Article
BioMedical Engineering Online, ISSN 1475-925X, 06/2016, Volume 15, Issue 1, p. 66
Journal Article
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