Results 161 to 170 of about 54,917 (203)

Bias-Reduced Localization for Drone Swarm Based on Sensor Selection. [PDF]

Sensors (Basel)
Wu B, Shen B, Zhang Y, Yang L, Wang Z.
europepmc   +1 more source

Spin-Bounded Correlations: Rotation Boxes Within and Beyond Quantum Theory. [PDF]

Commun Math Phys
Aloy A, Galley TD, Jones CL, Ludescher SL, Müller MP.   +4 more
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Evolving scientific discovery by unifying data and background knowledge with AI Hilbert. [PDF]

Nat Commun
Cory-Wright R, Cornelio C, Dash S, El Khadir B, Horesh L.   +4 more
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Semi-Device-Independent Randomness Expansion Using <i>n</i>→1 Parity-Oblivious Quantum Random Access Codes. [PDF]

Entropy (Basel)
Wang X, Chen X, Xu M, Mi W, Chen X.
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Positive Semidefinite Generalized Diffusion Tensor Imaging via Quadratic Semidefinite Programming

SIAM Journal on Imaging Sciences, 2013
The positive definiteness of a diffusion tensor is important in magnetic resonance imaging because it reflects the phenomenon of water molecular diffusion in complicated biological tissue environments. To preserve this property, we represent it as an explicit positive semidefinite (PSD) matrix constraint and some linear matrix equalities. The objective
Yannan Chen, Yuhong Dai, Deren Han, Wenyu Sun   +3 more
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Positive Semidefinite Pattern Decompositions

SIAM Journal on Matrix Analysis and Applications, 1990
Let \(A\) be a positive semidefinite matrix in a \(p\times p\) block tridiagonal form with square diagonal blocks, and let ...
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Positive semidefinite tensors

SCIENTIA SINICA Mathematica, 2016
In the era of big data, the high-order high-dimensional tensor structure has attracted more and more attention, which further leads to the extensive study on tensor theory, computation and applications. Analogous to the matrix case, the positive semidefinite tensors, which form an important class of tensors, have played an essential role in tensor ...
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Positive Semidefinite Matrices

2018
Positive semidefinite (PSD) and positive definite (PD) matrices are closely connected with Euclidean distance matrices. Accordingly, they play a central role in this monograph. This chapter reviews some of the basic results concerning these matrices.
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Semidefinite Programming in the Space of Partial Positive Semidefinite Matrices

SIAM Journal on Optimization, 2003
Summary: We build upon the work of \textit{M. Fukuda} et al. [SIAM J. Optim. 11, 647--674 (2001; Zbl 1010.90053)] and \textit{K. Nakata} et al. [Math. Program. 95, No. 2(B), 303--327 (2003; Zbl 1030.90081)], in which the theory of partial positive semidefinite matrices was applied to the semidefinite programming (SDP) problem as a technique for ...
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