A novel feature extraction method for roller bearing using sparse decomposition based on self-Adaptive complete dictionary
Sign Up to like & getrecommendations! Published in 2019 at "Measurement"
DOI: 10.1016/j.measurement.2019.106934
Abstract: Abstract Sparse decomposition based on complete dictionary can effectively extract impulse features from weak fault signals. However, compared with the over-complete dictionary, the complete dictionary no longer has redundancy features, and its robustness is reduced,… read more here.
Keywords: method; decomposition based; complete dictionary; adaptive complete ... See more keywords
Nonstationary signal extraction based on BatOMP sparse decomposition technique
Sign Up to like & getrecommendations! Published in 2021 at "Scientific Reports"
DOI: 10.1038/s41598-021-97431-z
Abstract: Sparse decomposition technique is a new method for nonstationary signal extraction in a noise background. To solve the problem of accuracy and efficiency exclusive in sparse decomposition, the bat algorithm combined with Orthogonal Matching Pursuits… read more here.
Keywords: decomposition technique; decomposition; nonstationary signal; sparse decomposition ... See more keywords
Ground penetrating radar clutter removal via randomized low rank and sparse decomposition for missing data case
Sign Up to like & getrecommendations! Published in 2020 at "International Journal of Remote Sensing"
DOI: 10.1080/01431161.2020.1763508
Abstract: ABSTRACT Dealing with ground penetrating radar (GPR) data with missing entries can affect the performance of clutter removal methods heavily, making target imaging/detection via GPR practically impossible. This paper proposes a two-step approach based on… read more here.
Keywords: missing data; rank sparse; decomposition; low rank ... See more keywords
Automatic Relevance Determination of Adaptive Variational Bayes Sparse Decomposition for Micro-Cracks Detection in Thermal Sensing
Sign Up to like & getrecommendations! Published in 2017 at "IEEE Sensors Journal"
DOI: 10.1109/jsen.2017.2722465
Abstract: Induction thermography has been applied as an emerging non-destructive testing and evaluation technique for a wide range of conductive materials. The infrared vision sensing acquired image sequences contain valuable information in both spatial and time… read more here.
Keywords: relevance determination; detection; adaptive variational; variational bayes ... See more keywords
Self-Adaptive Low-Rank and Sparse Decomposition for Hyperspectral Anomaly Detection
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"
DOI: 10.1109/jstars.2022.3172120
Abstract: Hyperspectral anomaly detection is a widely used technique for exploring target of interest in hyperspectral images (HSIs). In recent years, the low-rank and sparse-decomposition-based anomaly detection model has attracted extensive attention. However, these models suffer… read more here.
Keywords: hyperspectral anomaly; rank sparse; low rank; detection ... See more keywords
Regularized sparse decomposition model for speech enhancement via convex distortion measure
Sign Up to like & getrecommendations! Published in 2018 at "Modern Physics Letters B"
DOI: 10.1142/s0217984918502627
Abstract: An important stage in speech enhancement is to estimate noise signal which is a difficult task in non-stationary and low signal-to-noise conditions. This paper presents an iterative speech enhancem... read more here.
Keywords: decomposition model; regularized sparse; speech; speech enhancement ... See more keywords
Hyperspectral image compressed processing: Evolutionary multi-objective optimization sparse decomposition
Sign Up to like & getrecommendations! Published in 2022 at "PLoS ONE"
DOI: 10.1371/journal.pone.0267754
Abstract: In the compressed processing of hyperspectral images, orthogonal matching pursuit algorithm (OMP) can be used to obtain sparse decomposition results. Aimed at the time-complex and difficulty in applying real-time processing, an evolutionary multi-objective optimization sparse… read more here.
Keywords: multi objective; compressed processing; decomposition; sparse decomposition ... See more keywords