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Experimental and Machine Learning Study of a Modified Cymbal Piezoelectric Energy Harvester. [PDF]

Micromachines (Basel)
Seecharan T, Kiffmeyer C, Voiles N, Enrlichman K, Hankins A, Zhao P.   +5 more
europepmc   +1 more source

ePoster

European Journal of Neurology, Volume 33, Issue S1, June 2026.
wiley   +1 more source

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Applications of singular-value decomposition (SVD)

Mathematics and Computers in Simulation, 2004
This work, supported by the Russian Ministry of Education, proposes and illustrates the use of singular-value decomposition (SDV) in terms of \(2\times 2\) matrices, using the suggestive terms ``hanger'', ``aligner'', ``stretcher'' and claiming that the use of SVD in education is still in its infancy.
Gennadi Malaschonok
exaly   +3 more sources

Singular Value Decomposition (SVD) Image Coding

IRE Transactions on Communications Systems, 1976
The numerical techniques of transform image coding are well known in the image bandwidth compression literature. This concise paper presents a new transform method in which the singular values and singular vectors of an image are computed and transmitted instead of transform coefficients. The singular value decomposition (SVD) method is known to be the
H Andrews
exaly   +3 more sources

Substructuring technique: improvement by means of singular value decomposition (SVD)

Applied Acoustics, 2001
Abstract There are two classical methods used for the determination of the dynamic behaviour of a coupled structure: (a) analytical modeling and (b) experimental modal analysis. However, both these methods fail to give acceptable results due to various reasons.
D T Tsahalis
exaly   +3 more sources

Differentiable singular value decomposition (SVD)

Mechanical Systems and Signal Processing
Sicheng He, Rohit Kanchi
exaly   +3 more sources

Singular-Value Decomposition (SVD)

Encyclopedia of Parallel Computing, 2011
In the previous section, we utilized the orthogonal direct-sum decomposi- tions $$ E^n = V_1 \oplus W_{1\,\,} \,$$ and $$ E^m = V_2 \oplus W_2 $$ where\( V_1 = Sp(A),W_1 = {V_1}^ \bot,W_2 = Ker(A),\)and\( V_2 = {W_2}^{\bot,}\)to define the Moore-Penrose inverseA- of the n by m matrix A in \( y = Ax \) a linear transformation from \( E^m \,\)
Asnafiya Asrof, Rabbani Ischak, Gumgum Darmawan   +2 more
semanticscholar   +4 more sources

A Bearing Fault Diagnosis Method Based on Enhanced Singular Value Decomposition

IEEE Transactions on Industrial Informatics, 2021
For the two shortcomings of singular value decomposition (SVD), the determination of the reconstruction order and the poor noise reduction ability, an enhanced SVD is introduced in this article.
Tao Liu, Xing Wu
exaly   +2 more sources

Reactor noise analysis based on the singular value decomposition (SVD)

Annals of Nuclear Energy, 1998
Abstract This paper reviews different techniques to analyze BWR's stability regime from neutronic power signals, and alternative methodologies based on the singular value decomposition (SVD) of a given matrix are proposed. The results obtained from experimental signals using two different constructions of the embedding space of the system have been ...
J. Navarro-Esbrí, G. Verdú, D. Ginestar, J. Muñoz-Cobo   +3 more
semanticscholar   +2 more sources

Analysis of CATA data by Singular Value Decomposition (SVD)

, 2022
_ Data by CATA (Check-All-That-Apply) method was analyzed by SVD (Singular Value Decomposition). SVD extracts row and column informations of the cross table of CATA data. An example of SVD of a cross table, which is made of kinds of rice, column variables, and of questions, row variables, produced interesting results.
Yasuharu Okamoto
openaire   +2 more sources