![Fast iterative WSVT algorithm in WNN minimization problem for multiuser massive MIMO channel estimation - Vanidevi - 2018 - International Journal of Communication Systems - Wiley Online Library Fast iterative WSVT algorithm in WNN minimization problem for multiuser massive MIMO channel estimation - Vanidevi - 2018 - International Journal of Communication Systems - Wiley Online Library](https://onlinelibrary.wiley.com/cms/asset/5fa4c99f-7ec1-45b2-94d0-c841a3289ae8/dac3378-fig-0004-m.jpg)
Fast iterative WSVT algorithm in WNN minimization problem for multiuser massive MIMO channel estimation - Vanidevi - 2018 - International Journal of Communication Systems - Wiley Online Library
![Assessing the role of initial conditions in the local structural identifiability of large dynamic models | Scientific Reports Assessing the role of initial conditions in the local structural identifiability of large dynamic models | Scientific Reports](https://media.springernature.com/lw685/springer-static/image/art%3A10.1038%2Fs41598-021-96293-9/MediaObjects/41598_2021_96293_Fig4_HTML.png)
Assessing the role of initial conditions in the local structural identifiability of large dynamic models | Scientific Reports
![PDF] COMPARISON OF RANK REVEALING ALGORITHMS APPLIED TO MATRICES WITH WELL DEFINED NUMERICAL RANKS | Semantic Scholar PDF] COMPARISON OF RANK REVEALING ALGORITHMS APPLIED TO MATRICES WITH WELL DEFINED NUMERICAL RANKS | Semantic Scholar](https://d3i71xaburhd42.cloudfront.net/759536b0e6491825fce0b29f11520e6c95b79743/10-Figure5.2-1.png)
PDF] COMPARISON OF RANK REVEALING ALGORITHMS APPLIED TO MATRICES WITH WELL DEFINED NUMERICAL RANKS | Semantic Scholar
![AMT - Filling the gaps of in situ hourly PM2.5 concentration data with the aid of empirical orthogonal function analysis constrained by diurnal cycles AMT - Filling the gaps of in situ hourly PM2.5 concentration data with the aid of empirical orthogonal function analysis constrained by diurnal cycles](https://amt.copernicus.org/articles/13/1213/2020/amt-13-1213-2020-f09-high-res.png)
AMT - Filling the gaps of in situ hourly PM2.5 concentration data with the aid of empirical orthogonal function analysis constrained by diurnal cycles
![Distributions of the singular values of the modeling operator G in X... | Download Scientific Diagram Distributions of the singular values of the modeling operator G in X... | Download Scientific Diagram](https://www.researchgate.net/publication/347021853/figure/fig1/AS:1001540278038528@1615797218067/Distributions-of-the-singular-values-of-the-modeling-operator-G-in-X-polarization-Two.png)
Distributions of the singular values of the modeling operator G in X... | Download Scientific Diagram
![AMT - Filling the gaps of in situ hourly PM2.5 concentration data with the aid of empirical orthogonal function analysis constrained by diurnal cycles AMT - Filling the gaps of in situ hourly PM2.5 concentration data with the aid of empirical orthogonal function analysis constrained by diurnal cycles](https://amt.copernicus.org/articles/13/1213/2020/amt-13-1213-2020-f07-high-res.png)
AMT - Filling the gaps of in situ hourly PM2.5 concentration data with the aid of empirical orthogonal function analysis constrained by diurnal cycles
![Atmosphere | Free Full-Text | Gap-Filling of MODIS Time Series Land Surface Temperature (LST) Products Using Singular Spectrum Analysis (SSA) | HTML Atmosphere | Free Full-Text | Gap-Filling of MODIS Time Series Land Surface Temperature (LST) Products Using Singular Spectrum Analysis (SSA) | HTML](https://www.mdpi.com/atmosphere/atmosphere-09-00334/article_deploy/html/images/atmosphere-09-00334-g005.png)
Atmosphere | Free Full-Text | Gap-Filling of MODIS Time Series Land Surface Temperature (LST) Products Using Singular Spectrum Analysis (SSA) | HTML
![PDF] Spectral Gap Error Bounds for Improving CUR Matrix Decomposition and the Nyström Method | Semantic Scholar PDF] Spectral Gap Error Bounds for Improving CUR Matrix Decomposition and the Nyström Method | Semantic Scholar](https://d3i71xaburhd42.cloudfront.net/17d9e5bf60190174443db3963e0457cdbdafb927/2-Figure1-1.png)