With the advancement of technology, we are able to collect, store, and transmit an ever-increasing volume of data. However, our ability to extract useful patterns from this massive amount of data is still lagging behind. Machine learning and signal processing…

The limitations common to linear imaging techniques were formalized succinctly by Ernst Abbe in 1873. In his theory, each Fourier component of a signal propagates independently from the source to the detector, and the corresponding feature can be detected only…

Machine learning is the science of discovering knowledge from data and making decisions based on this learnt structure. It has grown into a broad discipline that has established many statistical and computational learning principles. We are surrounded by the applications…

The central goal of compressed sensing is to capture attributes of a signal using very few measurements. The initial publications by Donoho and by Candes and Tao have been followed by applications to image compression, data streaming, medical signal processing,…