Results 91 to 100 of about 62,622 (323)

Performance Analysis of SVD-assisted Downlink Multiuser MIMO Systems

, 2010
Multiuser multiple-input multiple-output (MIMO) downlink (DL) transmission schemes experience both multiuser interference as well as inter-antenna interference.
Ahrens, Andreas, Benavente Peces, César, Aust, Sebastian   +2 more
core  

QUANTUM SINGULAR VALUE DECOMPOSITION BASED APPROXIMATION ALGORITHM

, 2010
Singular Value Decomposition (SVD) is one of the most useful techniques for analyzing data in linear algebra. SVD decomposes a rectangular real or complex matrix into two orthogonal matrices and one diagonal matrix.
SANDOR IMRE, LASZLO GYONGYOSI
core   +1 more source

SimulScan and Partial Least Squares: Visualizing Swallowing Through Functional and Dynamic Imaging Correlations

Magnetic Resonance in Medicine, EarlyView.
ABSTRACT Purpose Swallowing involves the precise coordination of muscles and brain areas and can be disrupted in a variety of neurological conditions. Current methods to visualize swallowing cannot examine both the biomechanics and brain activity associated with specific swallowing events.
Bradley P. Sutton, Anthony Bosshardt, Ching‐Hsuan Peng, Ololade T. Adetula, Jiyoon Kim, Riwei Jin, Vaishnavi Krishna, William G. Pearson Jr., Zhongming Liu, Georgia A. Malandraki   +9 more
wiley   +1 more source

Robust recursive bi-iteration singular value decomposition (SVD) for subspace tracking and adaptive filtering [PDF]

, 2003
The recursive bi-iteration singular value decomposition (Bi-SVD), proposed by Strobach, is en efficient and well-structured algorithm for performing subspace tracking. Unfortunately, its performance under impulse noise environment degrades substantially.
Ho, KL, Wen, Y, Chan, SC
core   +1 more source

Imaging patterns and genetic associations of brain atrophy across distinct symptom stages in Parkinson's disease

Neuroprotection, EarlyView.
Early disease stages showed limited cortical atrophy and enrichment of synaptic and calcium signaling pathways, whereas advanced stages demonstrated widespread cortical degeneration associated with immune activation and extracellular matrix remodeling.
Yi Ji, Liujia Lu, Kaidong Chen, Ruixuan Zhang, Yao Lu, Yachen Shi, Xiangming Fang   +6 more
wiley   +1 more source

Iron-binding cellular profile of transferrin using label-free Raman hyperspectral imaging and singular value decomposition (SVD). [PDF]

Free Radic Biol Med, 2021
Tubbesing K, Khoo TC, Bahreini Jangjoo S, Sharikova A, Barroso M, Khmaladze A.   +5 more
europepmc   +1 more source

SVD-LSTM-based rainfall threshold prediction for rainfall-induced landslides in Chongqing

Geomatics, Natural Hazards & Risk
Rainfall-induced landslides in Chongqing, a region of significant interest due to its high incidence rate, have traditionally been predicted using empirical rainfall thresholds.
Chao He, Chaofan Wang, Junwen Peng, Wenhui Jiang, Jing Liu   +4 more
doaj   +1 more source

Impact of data assimilation on Arctic sea‐ice thickness variability and its coupling with atmospheric forcing

Quarterly Journal of the Royal Meteorological Society, EarlyView.
We document for the first time how the assimilation of CS2SMOS observations improves the model representation of Arctic sea‐ice thickness (SIT) and its variability: biases are reduced (top row), while excessive variability in the Beaufort Sea and lack of variability in the ice pack are both corrected (bottom row).
Jiping Xie, Yue Ying, Richard Davy, Laurent Bertino   +3 more
wiley   +1 more source

Componentwise Perturbation Analysis of the Singular Value Decomposition of a Matrix

Applied Sciences
A rigorous perturbation analysis is presented for the singular value decomposition (SVD) of a real matrix with full column rank. It is proved that the SVD perturbation problem is well posed only when the singular values are distinct.
Vera Angelova, Petko Petkov
doaj   +1 more source

Singular value decomposition of noisy data: noise filtering

Experiments in Fluids, 2019
The singular value decomposition (SVD) and proper orthogonal decomposition are widely used to decompose velocity field data into spatiotemporal modes.
Brenden P. Epps, E. Krivitzky
semanticscholar   +1 more source