Compressive sensing (CS) is a novel sampling paradigm that samples signals in a much
more efficient way than the established Nyquist sampling theorem. CS has recently gained a …

In digital signal processing (DSP), Nyquistrate sampling completely describes a signal by
exploiting its bandlimitedness. Compressed Sensing (CS), also known as compressive …

Compressive sensing is a new signal processing paradigm that aims to encode sparse
signals by using far lower sampling rates than those in the traditional Nyquist approach. It …

Compressive sensing (CS) is an alternative to Shannon/Nyquist sampling for the acquisition
of sparse or compressible signals that can be well approximated by just K¿ N elements from …

Compressive Sampling Page 1 Compressive Sampling [from the GUEST EDITORS] Richard G.
Baraniuk, Emmanuel Candès, Robert Nowak, and Martin Vetterli IEEE SIGNAL PROCESSING …

Recovering sparse signals from linear measurements has demonstrated outstanding utility
in a vast variety of real-world applications. Compressive sensing is the topic that studies the …

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 …

Compressive sensing is a new signal acquisition technology with the potential to reduce the
number of measurements required to acquire signals that are sparse or compressible in …

The Shannon/Nyquist sampling theorem tells us that in order to not lose information when
uniformly sampling a signal we must sample at least two times faster than its bandwidth. In …

Compressive sensing (CS) has drawn quite an amount of attention as a joint sampling and
compression approach. Its theory shows that when the signal is sparse enough in some …