skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.


Title: Impact of Channel and System Parameters on Performance Evaluation of Frequency Extrapolation Using Machine Learning
Award ID(s):
2008443 2229535
PAR ID:
10646159
Author(s) / Creator(s):
 ;  ;  
Publisher / Repository:
IEEE
Date Published:
Journal Name:
IEEE Open Journal of the Communications Society
Volume:
6
ISSN:
2644-125X
Page Range / eLocation ID:
4840 to 4853
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. null (Ed.)
  2. null (Ed.)
  3. null (Ed.)
  4. null (Ed.)
    A unified approach to the determination of eigenvalues and eigenvectors of specific matrices associated with directed graphs is presented. Matrices studied include the new distance matrix, with natural extensions to the distance Laplacian and distance signless Laplacian, in addition to the new adjacency matrix, with natural extensions to the Laplacian and signless Laplacian. Various sums of Kronecker products of nonnegative matrices are introduced to model the Cartesian and lexicographic products of digraphs. The Jordan canonical form is applied extensively to the analysis of spectra and eigenvectors. The analysis shows that Cartesian products provide a method for building infinite families of transmission regular digraphs with few distinct distance eigenvalues. 
    more » « less