Add to ORKGIncludes bibliographical references (page 43).Compressed Sensing technology is used in many applications and is a widely growing field that attracts researches. In this thesis, spectrum sensing is proposed and compared to existing HW and SW techniques that performs this function. The theory of Compressed Sensing will be covered and the limitations and conditions that play a big role are going to be presented
This book is aimed at presenting concepts, methods and algorithms ableto cope with undersampled and ...
Data compression technology is one of the effective measures to improve the wireless data transmiss...
Abstract: Due to increasing number of wireless services spectrum congestion is a major concern in bo...
Compressed Sensing is a new signal processing methodology that allows to reconstruct sparse signals ...
This paper investigates the application of a compressed sampling (CS) algorithm as a spectrum sensin...
We propose a method to reduce the spectrum noise when compressed sensing (CS) is applied to spectrum...
The classical Shannon/Nyquist sampling theorem tells us that in order to not lose information when u...
Around 2006 the signal processing community was thrilled when the concept of Compressed Sensing was ...
Compressive sampling (CS), or compressive sensing, has the ability for reconstructing a sparse signa...
Spectrum sensing is the most important component in the cognitive radio (CR) technology. Spectrum se...
In a scenario where a cognitive radio unit wishes to transmit, it needs to know over which frequency...
In the process of spectrum sensing applied to wireless communications, it is possible to build inter...
For cognitive radios (CRs), compressive sampling (CS) techniques have been utilized for spectrum sen...
Abstract Sparsity is an attribute present in a myriad of natural signals and systems, occurring eit...
Theoretical thesis.Bibliography: pages 149-163.1. Introduction -- 2. Literature review -- 3. Compres...
This book is aimed at presenting concepts, methods and algorithms ableto cope with undersampled and ...
Data compression technology is one of the effective measures to improve the wireless data transmiss...
Abstract: Due to increasing number of wireless services spectrum congestion is a major concern in bo...
Compressed Sensing is a new signal processing methodology that allows to reconstruct sparse signals ...
This paper investigates the application of a compressed sampling (CS) algorithm as a spectrum sensin...
We propose a method to reduce the spectrum noise when compressed sensing (CS) is applied to spectrum...
The classical Shannon/Nyquist sampling theorem tells us that in order to not lose information when u...
Around 2006 the signal processing community was thrilled when the concept of Compressed Sensing was ...
Compressive sampling (CS), or compressive sensing, has the ability for reconstructing a sparse signa...
Spectrum sensing is the most important component in the cognitive radio (CR) technology. Spectrum se...
In a scenario where a cognitive radio unit wishes to transmit, it needs to know over which frequency...
In the process of spectrum sensing applied to wireless communications, it is possible to build inter...
For cognitive radios (CRs), compressive sampling (CS) techniques have been utilized for spectrum sen...
Abstract Sparsity is an attribute present in a myriad of natural signals and systems, occurring eit...
Theoretical thesis.Bibliography: pages 149-163.1. Introduction -- 2. Literature review -- 3. Compres...
This book is aimed at presenting concepts, methods and algorithms ableto cope with undersampled and ...
Data compression technology is one of the effective measures to improve the wireless data transmiss...
Abstract: Due to increasing number of wireless services spectrum congestion is a major concern in bo...