Fault detection and diagnosis strategy based on a weighted and combined index in the residual subspace associated with PCA
Sign Up to like & getrecommendations! Published in 2018 at "Journal of Chemometrics"
DOI: 10.1002/cem.2981
Abstract: Process monitoring and diagnosis are crucial for efficient and optimal operation of a chemical plant. Most multivariate statistical process monitoring strategies, such as principal component analysis, kernel principal component analysis, and dynamic principal component analysis,… read more here.
Keywords: detection; index; diagnosis; principal component ... See more keywords
Just‐in‐time learning–multiple subspace support vector data description used for non‐Gaussian dynamic batch process monitoring
Sign Up to like & getrecommendations! Published in 2019 at "Journal of Chemometrics"
DOI: 10.1002/cem.3134
Abstract: Batch process data are time‐varying dynamic and non‐Gaussian distributed. In addition, for multivariate statistical process monitoring, their variability can be overwhelmed when considering local variability behavior. To address the abovementioned issues, an improved batch process… read more here.
Keywords: time; batch process; process; monitoring ... See more keywords
Optimized multi-axis spiral projection MR fingerprinting with subspace reconstruction for rapid whole-brain high-isotropic-resolution quantitative imaging.
Sign Up to like & getrecommendations! Published in 2022 at "Magnetic resonance in medicine"
DOI: 10.1002/mrm.29194
Abstract: PURPOSE To improve image quality and accelerate the acquisition of 3D MR fingerprinting (MRF). METHODS Building on the multi-axis spiral-projection MRF technique, a subspace reconstruction with locally low-rank constraint and a modified spiral-projection spatiotemporal encoding… read more here.
Keywords: reconstruction; spiral projection; resolution; subspace reconstruction ... See more keywords
MVTree for Hierarchical Network Representation Based on Geometric Algebra Subspace
Sign Up to like & getrecommendations! Published in 2018 at "Advances in Applied Clifford Algebras"
DOI: 10.1007/s00006-018-0855-x
Abstract: Most hierarchical representation methods are designed from engineering perspectives, lacking an appropriate mathematical foundation to integrate different problem definitions. To solve this problem, a hierarchical network representation model based on geometric algebra (GA) subspace is… read more here.
Keywords: network; based geometric; network representation; hierarchical network ... See more keywords
Rank–sparsity balanced representation for subspace clustering
Sign Up to like & getrecommendations! Published in 2018 at "Machine Vision and Applications"
DOI: 10.1007/s00138-018-0918-y
Abstract: Subspace learning has many applications such as motion segmentation and image recognition. The existing algorithms based on self-expressiveness of samples for subspace learning may suffer from the unsuitable balance between the rank and sparsity of… read more here.
Keywords: rank sparsity; representation; subspace; subspace clustering ... See more keywords
Subspace Codes in PG(2N − 1, Q)
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DOI: 10.1007/s00493-016-3354-5
Abstract: An (r,M,2δ;k)q constant-dimension subspace code, δ > 1, is a collection C of (k − 1)-dimensional projective subspaces of PG(r − 1,q) such that every (k − δ)-dimensional projective subspace of PG(r − 1,q) is… read more here.
Keywords: subspace code; dimension subspace; constant dimension; subspace codes ... See more keywords
Robust subspace learning-based low-rank representation for manifold clustering
Sign Up to like & getrecommendations! Published in 2018 at "Neural Computing and Applications"
DOI: 10.1007/s00521-018-3617-8
Abstract: Spectral clustering-based subspace clustering methods have attracted broad interest in recent years. This kind of methods usually uses the self-representation in the original space to extract the affinity between the data points. However, we can… read more here.
Keywords: rank representation; manifold clustering; subspace; low rank ... See more keywords
ASCRClu: an adaptive subspace combination and reduction algorithm for clustering of high-dimensional data
Sign Up to like & getrecommendations! Published in 2020 at "Pattern Analysis and Applications"
DOI: 10.1007/s10044-020-00884-7
Abstract: The curse of dimensionality in high-dimensional data is one of the major challenges in data clustering. Recently, a considerable amount of literature has been published on subspace clustering to address this challenge. The main objective… read more here.
Keywords: combination; high dimensional; subspace clustering; dimensional data ... See more keywords
Sparse large-margin nearest neighbor embedding via greedy dyad functional optimization
Sign Up to like & getrecommendations! Published in 2019 at "Applied Intelligence"
DOI: 10.1007/s10489-019-01472-x
Abstract: We consider the sparse subspace learning problem where the intrinsic subspace is assumed to be low-dimensional and formed by sparse basis vectors. Confined to a few sparse bases, projecting data to the learned subspace essentially… read more here.
Keywords: large margin; sparse; subspace; functional optimization ... See more keywords
Explaining anomalies in groups with characterizing subspace rules
Sign Up to like & getrecommendations! Published in 2018 at "Data Mining and Knowledge Discovery"
DOI: 10.1007/s10618-018-0585-7
Abstract: Anomaly detection has numerous applications and has been studied vastly. We consider a complementary problem that has a much sparser literature: anomaly description. Interpretation of anomalies is crucial for practitioners for sense-making, troubleshooting, and planning… read more here.
Keywords: anomalies groups; subspace; explaining anomalies; characterizing subspace ... See more keywords
Reactant subspaces and kinetics of chemical reaction networks
Sign Up to like & getrecommendations! Published in 2017 at "Journal of Mathematical Chemistry"
DOI: 10.1007/s10910-017-0809-x
Abstract: This paper studies a chemical reaction network’s (CRN) reactant subspace, i.e. the linear subspace generated by its reactant complexes, to elucidate its role in the system’s kinetic behaviour. We introduce concepts such as reactant rank… read more here.
Keywords: network; reactant subspaces; subspace; reaction ... See more keywords