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Latent variable regression and applications to planetary seismic instrumentation
2020
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The concept is first applied to combat the problem of ill-posed regression through the promising method of partial least squares (PLS). ...
The standard PLS algorithm is further generalised for complex-, quaternion- and tensor-valued data. ...
Mandic, "A Class of Multidimensional NIPALS Algorithms for Quaternion and Tensor Partial Least Squares Regression", Signal Processing , 160, 2019. 2. Alexander E. ...
doi:10.25560/79746
fatcat:vhz66sbgy5h6fazki2smo7qjre
Statistical signal processing of nonstationary tensor-valued data
2020
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
By introducing a model for the joint distribution of multiple random tensors, it is also possible to treat random tensor regression analyses and subspace methods within a unified separability framework ...
Both matrices and vectors are lower-order tensors, and this gives us a unique opportunity to consider some matrix signal processing models under the more powerful framework of multilinear tensor algebra ...
"A class of multidimensional
NIPALS algorithms for quaternion and tensor PLS-regression", Signal Processing,
vol. 160, pp. 316-327, 2019. ...
doi:10.25560/81087
fatcat:yswajb44jrh6fpgi4y4wt3hrcm