  Xampling generalizes compressed sensing (CS) to reduced-rate sampling of
analog signals. A unified framework is introduced for low rate sampling and
processing of signals lying in a union of subspaces. Xampling consists of two
main blocks: Analog compression that narrows down the input bandwidth prior to
sampling with commercial devices followed by a nonlinear algorithm that detects
the input subspace prior to conventional signal processing. A variety of analog
CS applications are reviewed within the unified Xampling framework including a
general filter-bank scheme for sparse shift-invariant spaces, periodic
nonuniform sampling and modulated wideband conversion for multiband
communications with unknown carrier frequencies, acquisition techniques for
finite rate of innovation signals with applications to medical and radar
imaging, and random demodulation of sparse harmonic tones. A hardware-oriented
viewpoint is advocated throughout, addressing practical constraints and
exemplifying hardware realizations where relevant. It will appear as a chapter
in a book on "Compressed Sensing: Theory and Applications" edited by Yonina
Eldar and Gitta Kutyniok.
