First Order and Second Order Learning Algorithms on the Special Orthogonal Group to Compute the SVD of Data Matrices

First Order and Second Order Learning Algorithms on the Special Orthogonal Group to Compute the SVD of Data Matrices

The present paper deals with neural algorithms to learn the singular value decomposition (SVD) of data matrices. The neural algorithms utilized in the present research endeavor were developed by Helmke and Moore (HM) and appear under the form of two continuous-time differential equations over the sp...

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Bibliographic Details
Main Authors: Simone Fiori, Lorenzo Del Rossi, Michele Gigli, Alessio Saccuti
Format: Article
Language:English
Published: MDPI AG 2020-02-01
Series:Electronics
Subjects:
singular value decomposition
initial value problem
first-order numerical method
second-order numerical method
manifold calculus and lie groups
learning system
internet of things
Online Access:https://www.mdpi.com/2079-9292/9/2/334

Internet

https://www.mdpi.com/2079-9292/9/2/334

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