1,008 research outputs found
A Primal-Dual Proximal Algorithm for Sparse Template-Based Adaptive Filtering: Application to Seismic Multiple Removal
Unveiling meaningful geophysical information from seismic data requires to
deal with both random and structured "noises". As their amplitude may be
greater than signals of interest (primaries), additional prior information is
especially important in performing efficient signal separation. We address here
the problem of multiple reflections, caused by wave-field bouncing between
layers. Since only approximate models of these phenomena are available, we
propose a flexible framework for time-varying adaptive filtering of seismic
signals, using sparse representations, based on inaccurate templates. We recast
the joint estimation of adaptive filters and primaries in a new convex
variational formulation. This approach allows us to incorporate plausible
knowledge about noise statistics, data sparsity and slow filter variation in
parsimony-promoting wavelet frames. The designed primal-dual algorithm solves a
constrained minimization problem that alleviates standard regularization issues
in finding hyperparameters. The approach demonstrates significantly good
performance in low signal-to-noise ratio conditions, both for simulated and
real field seismic data
On the effect of image denoising on galaxy shape measurements
Weak gravitational lensing is a very sensitive way of measuring cosmological
parameters, including dark energy, and of testing current theories of
gravitation. In practice, this requires exquisite measurement of the shapes of
billions of galaxies over large areas of the sky, as may be obtained with the
EUCLID and WFIRST satellites. For a given survey depth, applying image
denoising to the data both improves the accuracy of the shape measurements and
increases the number density of galaxies with a measurable shape. We perform
simple tests of three different denoising techniques, using synthetic data. We
propose a new and simple denoising method, based on wavelet decomposition of
the data and a Wiener filtering of the resulting wavelet coefficients. When
applied to the GREAT08 challenge dataset, this technique allows us to improve
the quality factor of the measurement (Q; GREAT08 definition), by up to a
factor of two. We demonstrate that the typical pixel size of the EUCLID optical
channel will allow us to use image denoising.Comment: Accepted for publication in A&A. 8 pages, 5 figure
MIMO-UFMC Transceiver Schemes for Millimeter Wave Wireless Communications
The UFMC modulation is among the most considered solutions for the
realization of beyond-OFDM air interfaces for future wireless networks. This
paper focuses on the design and analysis of an UFMC transceiver equipped with
multiple antennas and operating at millimeter wave carrier frequencies. The
paper provides the full mathematical model of a MIMO-UFMC transceiver, taking
into account the presence of hybrid analog/digital beamformers at both ends of
the communication links. Then, several detection structures are proposed, both
for the case of single-packet isolated transmission, and for the case of
multiple-packet continuous transmission. In the latter situation, the paper
also considers the case in which no guard time among adjacent packets is
inserted, trading off an increased level of interference with higher values of
spectral efficiency. At the analysis stage, the several considered detection
structures and transmission schemes are compared in terms of bit-error-rate,
root-mean-square-error, and system throughput. The numerical results show that
the proposed transceiver algorithms are effective and that the linear MMSE data
detector is capable of well managing the increased interference brought by the
removal of guard times among consecutive packets, thus yielding throughput
gains of about 10 - 13 . The effect of phase noise at the receiver is also
numerically assessed, and it is shown that the recursive implementation of the
linear MMSE exhibits some degree of robustness against this disturbance
- …