Wideband spectrum sensing is a critical component of a functioning cognitive radio system. Its major challenge is the too high sampling rate requirement. Compressive sensing (CS) promises to be able to deal with it. Nearly all the current CS based compressive wideband spectrum sensing methods exploit only the frequency sparsity to perform. Motivated by the achievement of a fast and robust detec...

This work develops novel algorithms for incorporating prior-support information into the field of One-Bit Compressed Sensing. Traditionally, Compressed Sensing is used for acquiring high-dimensional signals from few linear measurements. In applications, it is often the case that we have some knowledge of the structure of our signal(s) beforehand, and thus we would like to leverage it to attain ...

Recently with an emerging theory of ‘compressive sensing’ (CS), a radically new concept of compressive sensing radar (CSR) has been proposed in which the time-frequency plane is discretized into a grid. Random filtering is an interesting technique for efficiently acquiring signals in CS theory and can be seen as a linear time-invariant filter followed by decimation. In this paper, random filter...

The theory of compressive sensing (CS) has been employed to detect available spectrum resource in cognitive radio (CR) networks recently. Capitalizing on the spectrum resource underutilization and spatial sparsity of primary user (PU) locations, CS enables the identification of the unused spectrum bands and PU locations at a low sampling rate. Although CS has been studied in the cooperative spe...

of the Dissertation Fast and Robust Algorithms for Compressive Sensing and Other Applications

Compressive Sensing for 3D Data Processing Tasks: Applications, Models and Algorithms

Pattern-based Matrix-size Optimization Algorithm for Compressive Sensing in Real-world Body Sensor Networks

This document serves as a supplement to the material discussed in lecture 11. The document is not meant to be a comprehensive review of compressive sensing or compressive imaging. It is supposed to be an intuitive introduction to the basic mathematical concepts of compressive image reconstruction for the single pixel camera. More information can be found in the paper by Wakin et al. [2006], whi...

This document serves as a supplement to the material discussed in lecture 11. The document is not meant to be a comprehensive review of compressive sensing or compressive imaging. It is supposed to be an intuitive introduction to the basic mathematical concepts of compressive image reconstruction for the single pixel camera. More information can be found in the paper by Wakin et al. [2006], whi...

This document serves as a supplement to the material discussed in lecture 12. The document is not meant to be a comprehensive review of compressive sensing or compressive imaging. It is supposed to be an intuitive introduction to the basic mathematical concepts of compressive image reconstruction for the single pixel camera. More information can be found in the paper by Wakin et al. [2006], whi...