Results 51 to 60 of about 129,793 (292)
Data-driven pattern identification and outlier detection in time series [PDF]
, 2018 We address the problem of data-driven pattern identification and outlier detection in time series. To this end, we use singular value decomposition (SVD) which is a well-known technique to compute a low-rank approximation for an arbitrary matrix.
D Paul +7 more
core +3 more sources
Multimodal Data‐Driven Microstructure Characterization
Advanced Engineering Materials, EarlyView.A self‐consistent autonomous workflow for EBSP‐based microstructure segmentation by integrating PCA, GMM clustering, and cNMF with information‐theoretic parameter selection, requiring no user input. An optimal ROI size related to characteristic grain size is identified.
Qi Zhang +4 more
wiley +1 more source
Using singular value decomposition for generalized linear autoregression of signals
Current Directions in Biomedical Engineering, 2018 Autoregressive models (AR) are fundamental for analysis, representation, and prediction of signals. AR modelling uses the premise that past signal values influence current ones.
Schanze Thomas
doaj +1 more source
Multibiometric Identification System based on SVD and Wavelet Decomposition [PDF]
Engineering and Technology Journal, 2017 Biometric systems refer to the systems used for human recognition based on their characteristics. These systems are widely used in security institutions and access control.
M.N. Abdullah, H.A. Jeiad, R.A. Hussein
doaj +1 more source
Empirical Evaluation of Four Tensor Decomposition Algorithms [PDF]
, 2007 Higher-order tensor decompositions are analogous to the familiar Singular Value Decomposition (SVD), but they transcend the limitations of matrices (second-order tensors).
Turney, Peter D.
core +2 more sources
Advanced Functional Materials, EarlyView.Bioprosthetic aortic valves have revolutionized the treatment of aortic stenosis, but their durability is limited by structural valve deterioration (SVD). This review focuses on the pericardial tissue at the heart of these valves, examining how its mechanical properties and calcification drive fatigue and failure.
Gabriele Greco +7 more
wiley +1 more source
Robust Padé Approximation via SVD [PDF]
SIAM Review, 2013 Pade approximation is considered from the point of view of robust methods of numerical linear algebra, in particular, the singular value decomposition. This leads to an algorithm for practical computation that bypasses most problems of solution of nearly-singular systems and spurious pole-zero pairs caused by rounding errors, for which a MATLAB code is
Pedro Gonnet +2 more
openaire +2 more sources
Ferroelectric Quantum Dots for Retinomorphic In‐Sensor Computing
Advanced Materials, EarlyView.This work has provided a protocol for fabricating retinomorphic phototransistors by integrating ferroelectric ligands with quantum dots. The resulting device combines ferroelectricity, optical responsiveness, and low‐power operation to enable adaptive signal amplification and high recognition accuracy under low‐light conditions, while supporting ...
Tingyu Long +26 more
wiley +1 more source
A location and detection method for transient power quality disturbance using SVD-ILMD
Zhejiang dianliSwiftly and accurately analyze non-stationary disturbance signals within the power grid， a location and detection method for transient power quality disturbance that combines singular value decomposition （SVD） and improved local mean decomposition （ILMD）
CHENG Jiangzhou +5 more
doaj +1 more source
Robust Digital Watermarking on Vital Archives using Hybrid SVD and DWT Methods
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi), 2023 The development of Internet technology affects the dissemination of data, especially in vital government archives. This research uses a hybrid singular value decomposition (SVD) and discrete wavelet transform (DWT) method, which aims to protect the ...
Alita Wulan Dini +2 more
doaj +1 more source