Serving as a bridge between researchers in the computing domain and computing hardware designers, this book presents ReRAM techniques for distributed computing using IMC accelerators, ReRAM-based IMC architectures for machine learning (ML) and data-intensive applications, and st…
Chapter 8. Radar applications of compressive sensing by Albert G. Huizing and Reinier G. Tan Chapter 9. Advances in SAR change detection by Leslie M. Novak; Chapter 10. Future challenges by David Blacknell and Hugh Griffiths; Index. The ability to detect and locate targets by d…
The ability to detect and locate targets by day or night, over wide areas, regardless of weather conditions has long made radar a key sensor in many military and civil applications. However, the ability to automatically and reliably distinguish different targets represents a dif…
This thesis concerns the study of the statistics of natural images and compressive sensing for two main objectives: 1) to extend our understanding of the regularities exhibited by natural images of the visual world we regularly view around us, and 2) to incorporate this knowledg…
The growing adoption of data communication has resulted in dramatically higher capacity and performance. Communications engineers have historically optimized Physical (Phy)/Medium Access Control (MAC) layers to increase aggregate network throughput. However, in recent years, res…
Random signal measurement, in the form of random projections of signal vectors, extends the traditional point-wise and periodic schemes for signal sampling. In particular, the well-known problem of sensing sparse signals from linear measurements, also known as Compressed Sensing…