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 …

Recent years have seen significant advances in the study of symmetric informationally
complete (SIC) quantum measurements, also known as maximal sets of complex …

This comprehensive and engaging textbook introduces the basic principles and techniques
of signal processing, from the fundamental ideas of signals and systems theory to real-world …

One of the key challenges in the area of signal processing on graphs is to design
dictionaries and transform methods to identify and exploit structure in signals on weighted …

In this paper, we propose a new sparsity-based algorithm for automatic target detection in
hyperspectral imagery (HSI). This algorithm is based on the concept that a pixel in HSI lies in …

This book gives a unified introduction to the rapidly develo** area of finite tight frames.
Fifteen years ago, the existence of equal-norm tight frames of n> d vectors for Rd and Cd …

An emerging way to deal with high-dimensional noneuclidean data is to assume that the
underlying structure can be captured by a graph. Recently, ideas have begun to emerge …

We report on a new computer study of the existence of d 2 equiangular lines in d complex
dimensions. Such maximal complex projective codes are conjectured to exist in all finite …

A classic problem is the estimation of a set of parameters from measurements collected by
only a few sensors. The number of sensors is often limited by physical or economical …

Sulfated zirconia with S content of 2 wt.% equivalent to complete coverage of its surface was
studied by infrared spectroscopy. At least four sulfated species were identified and exhibited …