Cognitive radio technology has the potential to address the shortage of available radio
spectrum by enabling dynamic spectrum access. Since its introduction, researchers have …

Cognitive radio network (CRN) is a pioneering technology that was developed to improve
efficiency in spectrum utilization. It provides the secondary users with the privilege to …

Compressed sensing is a theory which can reconstruct an image almost perfectly with only a
few measurements by finding its sparsest representation. However, the computation time …

Spectrum sensing is an important process in cognitive radio. Spectrum sensing techniques
suffer from high processing time, hardware cost, and computational complexity. To address …

Compressive sensing involves 3 main processes: signal sparse representation, linear
encoding or measurement collection, and nonlinear decoding or sparse recovery. In the …

Sparse approximation addresses the problem of approximately fitting a linear model with a
solution having as few non-zero components as possible. While most sparse estimation …

We explore algorithms and limitations for sparse optimization problems such as sparse
linear regression and robust linear regression. The goal of the sparse linear regression …

Finding solutions to least-squares problems with low cardinality has found many
applications, including portfolio optimization, subset selection in statistics, and inverse …

压缩感知(Compressed sensing, CS) 技术是**几年出现的一种新兴的信号采样和压缩技术,
基于该理论所获得的原始信号采样值, 不仅数量大大低于基于传统的Nyquist 准则的采样值 …

This paper introduces a novel image encryption technique using Compressive Sensing (CS)
and DNA encoding. At first, the plain image is decomposed into the low and high-frequency …