Results 101 to 110 of about 1,611 (136)

Autoencoding-Assisted Quantum Cloning Machine. [PDF]

open access: yesEntropy (Basel)
Beh QJ   +4 more
europepmc   +1 more source

When noncanonical olfaction is optimal. [PDF]

open access: yesProc Natl Acad Sci U S A
Lienkaemper C, Younger MA, Ocker GK.
europepmc   +1 more source

A mechanistic theory of planning in prefrontal cortex

open access: yes
Jensen KT   +7 more
europepmc   +1 more source

Beyond alignment: synergistic integration is required for multimodal cell foundation models

open access: yes
Richter T   +7 more
europepmc   +1 more source

A Canonical CS Representation of a Pair of Subspaces

SIAM Journal on Matrix Analysis and Applications, 2016
Summary: Let \({\mathcal X}\) and \({\mathcal Y}\) be subspaces of \(\mathbb{R}^{n}\) of dimensions \(k\) and \(l\) with \(k\leq l\). Let \(X\) and \(Y\) be orthonormal bases for \({\mathcal X}\) and \({\mathcal Y}\). This paper describes canonical forms for \(X\) and \(Y\) under orthogonal transformations.
exaly   +3 more sources

A variational characterization of canonical angles between subspaces

Journal of Geometry, 2003
The min-max characterization is given for canonical (or principal) angles between two subspaces of an \(n\)-dimensional unitary space using recursively constructed pairs of vectors from inner products.
Vladimir Rakocevic   +2 more
exaly   +2 more sources

Cyclic Subspaces, Duality and the Jordan Canonical Form

Springer Undergraduate Mathematics Series, 2015
In this chapter we use the duality theory to analyze the properties of an endomorphism f on a finite dimensional vector space \(\mathcal V\) in detail. We are particularly interested in the algebraic and geometric multiplicities of the eigenvalues of f and the characterization of the corresponding eigenspaces.
Volker Mehrmann   +2 more
exaly   +2 more sources

Canonical relations of subspaces in multi-sensor data analysis

2014 22nd Signal Processing and Communications Applications Conference (SIU), 2014
In multisensor data analysis, scene details can be extracted via subspace methods without any prior information on the scene. In these decomposition techniques, data is projected into a new space so that the information in the data is highlighted. In this study, Principal Component Analysis, Independent Component Analysis and Minumum Noise Fractions ...
Ozgur Murat Polat, Yakup S. Özkazanç
exaly   +2 more sources

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