Water entry sound detection in strong noise by using the spectrogram matrix decomposition method
Sign Up to like & getrecommendations! Published in 2020 at "Applied Acoustics"
DOI: 10.1016/j.apacoust.2019.107171
Abstract: Abstract The water entry transient sound of a projectile can be used for early target detection in passive sonar. Two detectors for the transient sound with low Signal to Noise Ratios (SNRs) have been proposed… read more here.
Keywords: detection; matrix; detector; matrix decomposition ... See more keywords
Estimation of heteroscedasticity by local composite quantile regression and matrix decomposition
Sign Up to like & getrecommendations! Published in 2018 at "Journal of Nonparametric Statistics"
DOI: 10.1080/10485252.2017.1418869
Abstract: ABSTRACT We propose a two-step estimation method for nonparametric model with heteroscedasticity to estimate the scale function and the location function simultaneously. The local composite quantile regression (LCQR) is employed in the first step, and… read more here.
Keywords: quantile regression; heteroscedasticity; matrix decomposition; composite quantile ... See more keywords
Matrix Decomposition-Based Adaptive Control of Noncanonical Form MIMO DT Nonlinear Systems
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Automatic Control"
DOI: 10.1109/tac.2021.3115850
Abstract: This article presents a new study on adaptive control of multi-input and multi-output (MIMO) discrete-time nonlinear systems with a noncanonical form involving parametric uncertainties. The adaptive control scheme employs a vector relative degree formulation to… read more here.
Keywords: form; control; adaptive control; nonlinear systems ... See more keywords
Hybrid Matrix-Decomposition-Based Fast Direct Solver of Integral Equations
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Transactions on Antennas and Propagation"
DOI: 10.1109/tap.2021.3076351
Abstract: Our numerical experiments show that the hierarchical matrix (H-matrix) solver is more efficient than the butterfly solver for electrically small problems, although the converse is true for sufficiently large problems. In this communication, we propose… read more here.
Keywords: decomposition; matrix; matrix decomposition; decomposition based ... See more keywords
WHT and Matrix Decomposition-Based Approximated IDCT Architecture for HEVC
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Transactions on Circuits and Systems II: Express Briefs"
DOI: 10.1109/tcsii.2018.2874071
Abstract: This brief proposes a new model of inverse discrete cosine transform (IDCT) kernel for high efficiency video coding (HEVC). The kernel supports IDCT of order 4, 8, 16, and 32. The proposed architecture uses the… read more here.
Keywords: idct architecture; matrix decomposition; architecture; decomposition based ... See more keywords
ADMM-HFNet: A Matrix Decomposition-Based Deep Approach for Hyperspectral Image Fusion
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2021.3112181
Abstract: Hyperspectral image (HSI) fusion refers to the reconstruction of a high-resolution HSI by fusing a low-resolution HSI (LR-HSI) and a high-resolution multispectral image (HR-MSI) over the same scene. Recently, researchers have proposed many approaches to… read more here.
Keywords: admm hfnet; decomposition; hsi; hyperspectral image ... See more keywords
Iteratively Reweighted Minimax-Concave Penalty Minimization for Accurate Low-rank Plus Sparse Matrix Decomposition.
Sign Up to like & getrecommendations! Published in 2021 at "IEEE transactions on pattern analysis and machine intelligence"
DOI: 10.1109/tpami.2021.3122259
Abstract: Low-rank plus sparse matrix decomposition (LSD) is an important problem in computer vision and machine learning. It has been solved using convex relaxations of the matrix rank and l0-pseudo-norm, which are the nuclear norm and… read more here.
Keywords: low rank; matrix decomposition; rank; plus sparse ... See more keywords
Near-Optimal Hybrid Processing for Massive MIMO Systems via Matrix Decomposition
Sign Up to like & getrecommendations! Published in 2017 at "IEEE Transactions on Signal Processing"
DOI: 10.1109/tsp.2017.2699643
Abstract: For practical implementation of massive multiple-input multiple-output (MIMO) systems, the hybrid processing (precoding/combining) structure is promising to reduce the high implementation cost and power consumption rendered by large number of radio frequency (RF) chains of… read more here.
Keywords: massive mimo; matrix decomposition; hybrid processing; mimo systems ... See more keywords
MDHGI: Matrix Decomposition and Heterogeneous Graph Inference for miRNA-disease association prediction
Sign Up to like & getrecommendations! Published in 2018 at "PLoS Computational Biology"
DOI: 10.1371/journal.pcbi.1006418
Abstract: Recently, a growing number of biological research and scientific experiments have demonstrated that microRNA (miRNA) affects the development of human complex diseases. Discovering miRNA-disease associations plays an increasingly vital role in devising diagnostic and therapeutic… read more here.
Keywords: disease; association; matrix decomposition; least one ... See more keywords
SCCPMD: Probability matrix decomposition method subject to corrected similarity constraints for inferring long non-coding RNA–disease associations
Sign Up to like & getrecommendations! Published in 2023 at "Frontiers in Microbiology"
DOI: 10.3389/fmicb.2022.1093615
Abstract: Accumulating evidence has demonstrated various associations of long non-coding RNAs (lncRNAs) with human diseases, such as abnormal expression due to microbial influences that cause disease. Gaining a deeper understanding of lncRNA–disease associations is essential for… read more here.
Keywords: similarity; disease; lncrna disease; disease associations ... See more keywords
Double-Matrix Decomposition Image Steganography Scheme Based on Wavelet Transform with Multi-Region Coverage
Sign Up to like & getrecommendations! Published in 2022 at "Entropy"
DOI: 10.3390/e24020246
Abstract: 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 images… read more here.
Keywords: wavelet; region; decomposition; image ... See more keywords