Compressive Sensing (CS) is a new sensing modality, which compresses the signal being
acquired at the time of sensing. Signals can have sparse or compressible representation …

Due to the under-utilization problem of the allocated radio spectrum, cognitive radio (CR)
communications have recently emerged as a reliable and effective solution. Among various …

Data-driven discovery is revolutionizing how we model, predict, and control complex
systems. Now with Python and MATLAB®, this textbook trains mathematical scientists and …

The integration of data and scientific computation is driving a paradigm shift across the
engineering, natural, and physical sciences. Indeed, there exists an unprecedented …

This tutorial text gives a unifying perspective on machine learning by covering both
probabilistic and deterministic approaches-which are based on optimization techniques …

This first chapter formulates the objectives of compressive sensing. It introduces the
standard compressive problem studied throughout the book and reveals its ubiquity in many …

Nowadays, a large amount of information has to be transmitted or processed. This implies
high-power processing, large memory density, and increased energy consumption. In …

This paper investigates the problem of estimating the frequency components of a mixture of
s complex sinusoids from a random subset of n regularly spaced samples. Unlike previous …

Cognitive radio has emerged as one of the most promising candidate solutions to improve
spectrum utilization in next generation cellular networks. A crucial requirement for future …

Compressed sensing (CS) is an emerging field that has attracted considerable research
interest over the past few years. Previous review articles in CS limit their scope to standard …