This book details some of the major developments in the implementation of compressive sensing in radio applications for electronic defense and warfare communication use. It provides a comprehensive background to the subject and at the same time describes some novel algorithms. It also investigates application value and performance-related parameters of compressive sensing in scenarios such as direction finding, spectrum monitoring, detection, and classification
Thesis (Ph.D.)--University of Washington, 2013According to Nyquist Sampling theorem, a band-limited ...
International audienceThe paradigm of Compressive Sensing (CS) has emerged in the last few years as ...
In spectrum sensing and wireless communications analysis, signals of interest typically occupy only ...
This paper presents the application of Compressive Sensing (CS) theory in radar signal processing. C...
In this paper we give a brief review of compressive sensing (CS) applied to radar. Though CS theory ...
This paper presents the application of Compressive Sensing (CS) theory in radar signal processing. C...
Compressive sensing (CS) techniques offer a framework for the detection and allocation of sparse sig...
Compressive sensing is a relatively new technique in the signal processing field which allows acquir...
Sensing applications in Homeland Security have increasingly emphasized the use of high frequency RF ...
Abstract: Due to increasing number of wireless services spectrum congestion is a major concern in bo...
This thesis develops algorithms and applications for compressive sensing, a topic in signal processi...
In recent years, compressive sensing has received a lot of attention due to its ability to reduce th...
Compressive sensing (CS) is a new paradigm in signal processing and sampling theory. In this chapter...
Abstract—We describe a method of integrating Karhunen-Loève Transform (KLT) into compressive sensin...
Compressive Sensing (CS) has received much attention in several fields such as digital image process...
Thesis (Ph.D.)--University of Washington, 2013According to Nyquist Sampling theorem, a band-limited ...
International audienceThe paradigm of Compressive Sensing (CS) has emerged in the last few years as ...
In spectrum sensing and wireless communications analysis, signals of interest typically occupy only ...
This paper presents the application of Compressive Sensing (CS) theory in radar signal processing. C...
In this paper we give a brief review of compressive sensing (CS) applied to radar. Though CS theory ...
This paper presents the application of Compressive Sensing (CS) theory in radar signal processing. C...
Compressive sensing (CS) techniques offer a framework for the detection and allocation of sparse sig...
Compressive sensing is a relatively new technique in the signal processing field which allows acquir...
Sensing applications in Homeland Security have increasingly emphasized the use of high frequency RF ...
Abstract: Due to increasing number of wireless services spectrum congestion is a major concern in bo...
This thesis develops algorithms and applications for compressive sensing, a topic in signal processi...
In recent years, compressive sensing has received a lot of attention due to its ability to reduce th...
Compressive sensing (CS) is a new paradigm in signal processing and sampling theory. In this chapter...
Abstract—We describe a method of integrating Karhunen-Loève Transform (KLT) into compressive sensin...
Compressive Sensing (CS) has received much attention in several fields such as digital image process...
Thesis (Ph.D.)--University of Washington, 2013According to Nyquist Sampling theorem, a band-limited ...
International audienceThe paradigm of Compressive Sensing (CS) has emerged in the last few years as ...
In spectrum sensing and wireless communications analysis, signals of interest typically occupy only ...