Compressive sensing generally relies on the ℓ 2 norm for data fidelity, whereas in many
applications, robust estimators are needed. Among the scenarios in which robust …

A new approach to modulation classification based on the Kolmogorov-Smirnov (KS) test is
proposed. The KS test is a non-parametric method to measure the goodness of fit. The basic …

The restoration of blurred images corrupted with impulse noise is a difficult problem which
has been considered in a series of recent papers. These papers tackle the problem by using …

Impulsive or heavy-tailed processes with infinite variance appear naturally in a variety of
practical problems that include wireless communications, teletraffic, hydrology, geology, and …

Nonlinear filtering techniques based on the theory of robust estimation are introduced. Some
deterministic and asymptotic properties are derived. The proposed denoising methods are …

Standard-setting, groundbreaking, authoritative, comprehensive—these often overused
words perfectly describe The Circuits and Filters Handbook, Third Edition. This standard …

Recent results in compressed sensing show that a sparse or compressible signal can be
reconstructed from a few incoherent measurements. Since noise is always present in …

Digital signal processing for Global Navigation Satellite System (GNSS) receivers is mostly
based on the assumption that the noise at the receiver input is Gaussian. This assumption …

Culled from the pages of CRC's highly successful, best-selling The Circuits and Filters
Handbook, Second Edition, Passive, Active, and Digital Filters presents a sharply focused …

The restoration of images degraded by blurring and noise is one of the most important tasks
in image processing. In this paper, based on the total variation (TV) we propose a new …