Dynamics of typical Baire-1 functions on a compact $${{\varvec{n}}}$$n-manifold
Sign Up to like & getrecommendations! Published in 2019 at "Aequationes mathematicae"
DOI: 10.1007/s00010-019-00640-1
Abstract: Let M be a compact n-dimensional manifold with $$ bB_{1} $$bB1 the set of Baire-1 self-maps of M. For $$f\in bB_{1}$$f∈bB1, let $$\Omega (f)=\{\omega (x,f):x\in M\}$$Ω(f)={ω(x,f):x∈M} be the collection of $$\omega $$ω-limit sets generated by… read more here.
Keywords: manifold; omega limit; baire; lambda ... See more keywords
On the geometric order of totally nondegenerate CR manifolds
Sign Up to like & getrecommendations! Published in 2019 at "Mathematische Zeitschrift"
DOI: 10.1007/s00209-019-02415-5
Abstract: A CR manifold $M$, with CR distribution $\mathcal D^{10}\subset T^\mathbb C M$, is called {\it totally nondegenerate of depth $\mu$} if: (a) the complex tangent space $T^\mathbb C M$ is generated by all complex vector… read more here.
Keywords: geometric order; totally nondegenerate; manifold; order totally ... See more keywords
Existence of HKT metrics on hypercomplex manifolds of real dimension 8
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DOI: 10.1016/j.aim.2017.09.020
Abstract: Abstract A hypercomplex manifold M is a manifold equipped with three complex structures I , J , K satisfying quaternionic relations. Such a manifold admits a canonical torsion-free connection preserving the quaternion action, called the… read more here.
Keywords: hypercomplex manifolds; existence hkt; hkt metrics; manifold ... See more keywords
A mononuclear Co(ii) complex formed from pyridinedimethanol with manifold slow relaxation channels.
Sign Up to like & getrecommendations! Published in 2017 at "Dalton transactions"
DOI: 10.1039/c7dt02131c
Abstract: A mononuclear hexacoordinate complex [Co(pydm)2](dnbz)2 formed from 2,6-pyridinedimethanol in the coordination sphere of Co(ii) and dinitrobenzoato anions exhibits magnetic anisotropy of an easy axis type and a field induced slow magnetic relaxation with manifold relaxation… read more here.
Keywords: relaxation; mononuclear complex; relaxation channels; complex formed ... See more keywords
Initializing LSTM internal states via manifold learning
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DOI: 10.1063/5.0055371
Abstract: We present an approach, based on learning an intrinsic data manifold, for the initialization of the internal state values of long short-term memory (LSTM) recurrent neural networks, ensuring consistency with the initial observed input data.… read more here.
Keywords: lstm internal; initializing lstm; via manifold; states via ... See more keywords
Design and thermal analysis of coated and uncoated exhaust manifold
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DOI: 10.1080/01430750.2018.1456969
Abstract: ABSTRACT The exhaust manifold is used to collect and deliver waste toxic gases through a single pipe. During this process, the exhaust manifold suffers from the thermal stresses causes blowholes on the manifold. In this… read more here.
Keywords: manifold; coated uncoated; thermal analysis; exhaust manifold ... See more keywords
MRI Reconstruction From Sparse K-Space Data Using Low Dimensional Manifold Model
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Access"
DOI: 10.1109/access.2019.2925051
Abstract: Recent compressed sensing (CS) approaches to utilize the similarity and redundancy of magnetic resonance (MR) image patches to enable reconstruction from sparse k-space measurements. In this paper, the patches’ similarity and redundancy are exploited by… read more here.
Keywords: manifold; reconstruction sparse; dimensional manifold; low dimensional ... See more keywords
Modified Label Propagation on Manifold With Applications to Fault Classification
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DOI: 10.1109/access.2020.2995399
Abstract: In process monitoring, fault classification performance heavily relies on the labels of training data. However, the labeled data are inadequate and difficult to obtain because they require experienced human annotators. In this paper, a modified… read more here.
Keywords: label propagation; propagation; manifold; fault classification ... See more keywords
Generalized Learning Vector Quantization With Log-Euclidean Metric Learning on Symmetric Positive-Definite Manifold.
Sign Up to like & getrecommendations! Published in 2022 at "IEEE transactions on cybernetics"
DOI: 10.1109/tcyb.2022.3178412
Abstract: In many classification scenarios, the data to be analyzed can be naturally represented as points living on the curved Riemannian manifold of symmetric positive-definite (SPD) matrices. Due to its non-Euclidean geometry, usual Euclidean learning algorithms… read more here.
Keywords: lem; metric learning; distance; geometry ... See more keywords
Deep Manifold-to-Manifold Transforming Network for Skeleton-Based Action Recognition
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DOI: 10.1109/tmm.2020.2966878
Abstract: In this paper, we will investigate skeleton-based action recognition by employing high-order statistics feature and first-order statistics feature, where the high-order statistics feature is characterized by symmetric positive definite (SPD) matrices. Noting that SPD matrices… read more here.
Keywords: layer; action recognition; manifold; network ... See more keywords
SurReal: Complex-Valued Learning as Principled Transformations on a Scaling and Rotation Manifold.
Sign Up to like & getrecommendations! Published in 2020 at "IEEE transactions on neural networks and learning systems"
DOI: 10.1109/tnnls.2020.3030565
Abstract: Complex-valued data are ubiquitous in signal and image processing applications, and complex-valued representations in deep learning have appealing theoretical properties. While these aspects have long been recognized, complex-valued deep learning continues to lag far behind… read more here.
Keywords: valued data; deep learning; scaling rotation; complex valued ... See more keywords