Results 1 to 10 of about 3,813,510 (369)
Double-Matrix Decomposition Image Steganography Scheme Based on Wavelet Transform with Multi-Region Coverage. [PDF]
Entropy (Basel), 2022 On the basis of ensuring the quality and concealment of steganographic images, this paper proposes a double-matrix decomposition image steganography scheme with multi-region coverage, to solve the problem of poor extraction ability of steganographic ...
Pan P, Wu Z, Yang C, Zhao B.
europepmc +2 more sources
Optimal CUR Matrix Decompositions [PDF]
Proceedings of the forty-sixth annual ACM symposium on Theory of computing, 2014 The CUR decomposition of an $m \times n$ matrix $A$ finds an $m \times c$ matrix $C$ with a subset of $c < n$ columns of $A,$ together with an $r \times n$ matrix $R$ with a subset of $r < m$ rows of $A,$ as well as a $c \times r$ low-rank matrix $U ...
Boutsidis C. +4 more
core +4 more sources
MDHGI: Matrix Decomposition and Heterogeneous Graph Inference for miRNA-disease association prediction. [PDF]
PLoS Comput Biol, 2018 Recently, a growing number of biological research and scientific experiments have demonstrated that microRNA (miRNA) affects the development of human complex diseases.
Chen X, Yin J, Qu J, Huang L.
europepmc +2 more sources
Identification and Analysis of Human Microbe-Disease Associations by Matrix Decomposition and Label Propagation. [PDF]
Front Microbiol, 2019 Studies have shown that microbes exist widely in the human body and are closely related to human complex diseases. Predicting potential associations between microbes and diseases is conducive to understanding the mechanisms of complex diseases and can ...
Qu J, Zhao Y, Yin J.
europepmc +2 more sources
Beyond Low Rank + Sparse: Multi-scale Low Rank Matrix Decomposition. [PDF]
IEEE J Sel Top Signal Process, 2016 We present a natural generalization of the recent low rank + sparse matrix decomposition and consider the decomposition of matrices into components of multiple scales.
Ong F, Lustig M.
europepmc +2 more sources
Nonlocal low-rank and sparse matrix decomposition for spectral CT reconstruction. [PDF]
Inverse Probl, 2018 Niu S, Yu G, Ma J, Wang J.
europepmc +2 more sources
Mathematical Modelling and Control, 2023 This paper investigated the Kronecker product (KP) decomposition of the Boolean matrix and analyzed the topological structure of Kronecker product Boolean networks (KPBNs).
Xiaomeng Wei, Haitao Li, Guodong Zhao
doaj +1 more source
Singular Value Decomposition of Spatial Matrices
Современные информационные технологии и IT-образование, 2022 Singular value decomposition is a basic building block which is used in solution of many different problems. In cases when dimensionality of a problem exceeds two, a generalization of a singular value decomposition – tensor decompositions – are used ...
Pavel Iljin, Tatiana Samoilova
doaj +1 more source
Energy-Based Adaptive CUR Matrix Decomposition
IEEE Access, 2023 CUR decompositions are interpretable data analysis tools that express a data matrix in terms of a small number of actual columns and/or actual rows of the data matrix.
Liwen Xu, Xuejiao Zhao, Yongxia Zhang
doaj +1 more source
A Watermarking Optimization Method Based on Matrix Decomposition and DWT for Multi-Size Images
Electronics, 2022 Image watermarking is a key technology for copyright protection, and how to better balance the invisibility and robustness of algorithms is a challenge.
Lei Wang, Huichao Ji
semanticscholar +1 more source