Inscrição na biblioteca: Guest
Portal Digital Begell Biblioteca digital da Begell eBooks Diários Referências e Anais Coleções de pesquisa
Telecommunications and Radio Engineering
SJR: 0.203 SNIP: 0.44 CiteScore™: 1

ISSN Imprimir: 0040-2508
ISSN On-line: 1943-6009

Volume 79, 2020 Volume 78, 2019 Volume 77, 2018 Volume 76, 2017 Volume 75, 2016 Volume 74, 2015 Volume 73, 2014 Volume 72, 2013 Volume 71, 2012 Volume 70, 2011 Volume 69, 2010 Volume 68, 2009 Volume 67, 2008 Volume 66, 2007 Volume 65, 2006 Volume 64, 2005 Volume 63, 2005 Volume 62, 2004 Volume 61, 2004 Volume 60, 2003 Volume 59, 2003 Volume 58, 2002 Volume 57, 2002 Volume 56, 2001 Volume 55, 2001 Volume 54, 2000 Volume 53, 1999 Volume 52, 1998 Volume 51, 1997

Telecommunications and Radio Engineering

DOI: 10.1615/TelecomRadEng.v56.i4-5.170
6 pages

The Application of the Permutation Filters for Adaptive Digital Quadratic Detector

Victor Golikov
Universidad Autonoma del Carmen,Ciudad del Carmen, Campeche, Mexico
Olga Lebedeva
Universidad Autonoma del Carmen, Ciudad del Carmen, Campeche, Mexico
Jose Luis Orta
Director of Department of Universidad Autonoma del Carmen, Ciudad del Carmen, Campeche, Mexico


This paper proposes a method to reduce the computational complexity of the optimal digital quadratic detector, which is the optimal Neyman-Pearson detector for detecting a colored Gaussian random target signal against colored Gaussian distributed noise. The covariance matrices of the colored noise are unknown. We also presents fully adaptive detector and it exhibits an acceptable loss with respect to previously proposed adaptive detector. This detector has been constructed by replacing the covariant matrices on the appropriate block-circulant matrices in the likelihood ratio for example dyadic matrices. The performance comparison between the classical adaptive approach and the adaptive approach proposed by the authors carried out in terms of probability of detection as a function of the signal to noise ratio for a fixed probability of false alarm and in term of computational complexity.

Articles with similar content:

Low-Rank Quadratic Detector of Random Signals in Unknown Correlated Clutter
Telecommunications and Radio Engineering, Vol.67, 2008, issue 18
Olga Lebedeva, Victor Golikov
Modeling in Class of Systems of Regression Equations with Random Coefficients under Conditions of Structural Uncertainty
Journal of Automation and Information Sciences, Vol.40, 2008, issue 4
Alexander P. Sarychev
Neurofuzzy Algorithm For Channel Equalization
Telecommunications and Radio Engineering, Vol.56, 2001, issue 4&5
Jose Ambrosio Bastian, Mariko Nakano Miyatake, Hector Manuel Perez-Meana
Recognition of the Binary Signals in Non-Gaussian Hindrances
Journal of Automation and Information Sciences, Vol.31, 1999, issue 12
Yuriy G. Lega
Telecommunications and Radio Engineering, Vol.74, 2015, issue 18
V. V. Abramova