7,917 research outputs found
Multi-Detector Multi-Component spectral matching and applications for CMB data analysis
We present a new method for analyzing multi--detector maps containing
contributions from several components. Our method, based on matching the data
to a model in the spectral domain, permits to estimate jointly the spatial
power spectra of the components and of the noise, as well as the mixing
coefficients. It is of particular relevance for the analysis of
millimeter--wave maps containing a contribution from CMB anisotropies.Comment: 15 pages, 7 Postscript figures, submitted to MNRA
Precoder design for space-time coded systems over correlated Rayleigh fading channels using convex optimization
A class of computationally efficient linear precoders for space-time block coded multiple-input multiple-output wireless systems is derived based on the minimization of the exact symbol error rate (SER) and its upper bound. Both correlations at the transmitter and receiver are assumed to be present, and only statistical channel state information in the form of the transmit and receive correlation matrices is assumed to be available at the transmitter. The convexity of the design based on SER minimization is established and exploited. The advantage of the developed technique is its low complexity. We also find various relationships of the proposed designs to the existing precoding techniques, and derive very simple closed-form precoders for special cases such as two or three receive antennas and constant receive correlation. The numerical simulations illustrate the excellent SER performance of the proposed precoders
Imaging of buried objects from experimental backscattering time dependent measurements using a globally convergent inverse algorithm
We consider the problem of imaging of objects buried under the ground using
backscattering experimental time dependent measurements generated by a single
point source or one incident plane wave. In particular, we estimate dielectric
constants of those objects using the globally convergent inverse algorithm of
Beilina and Klibanov. Our algorithm is tested on experimental data collected
using a microwave scattering facility at the University of North Carolina at
Charlotte. There are two main challenges working with this type of experimental
data: (i) there is a huge misfit between these data and computationally
simulated data, and (ii) the signals scattered from the targets may overlap
with and be dominated by the reflection from the ground's surface. To overcome
these two challenges, we propose new data preprocessing steps to make the
experimental data to be approximately the same as the simulated ones, as well
as to remove the reflection from the ground's surface. Results of total 25 data
sets of both non blind and blind targets indicate a good accuracy.Comment: 34 page
Sparse and Non-Negative BSS for Noisy Data
Non-negative blind source separation (BSS) has raised interest in various
fields of research, as testified by the wide literature on the topic of
non-negative matrix factorization (NMF). In this context, it is fundamental
that the sources to be estimated present some diversity in order to be
efficiently retrieved. Sparsity is known to enhance such contrast between the
sources while producing very robust approaches, especially to noise. In this
paper we introduce a new algorithm in order to tackle the blind separation of
non-negative sparse sources from noisy measurements. We first show that
sparsity and non-negativity constraints have to be carefully applied on the
sought-after solution. In fact, improperly constrained solutions are unlikely
to be stable and are therefore sub-optimal. The proposed algorithm, named nGMCA
(non-negative Generalized Morphological Component Analysis), makes use of
proximal calculus techniques to provide properly constrained solutions. The
performance of nGMCA compared to other state-of-the-art algorithms is
demonstrated by numerical experiments encompassing a wide variety of settings,
with negligible parameter tuning. In particular, nGMCA is shown to provide
robustness to noise and performs well on synthetic mixtures of real NMR
spectra.Comment: 13 pages, 18 figures, to be published in IEEE Transactions on Signal
Processin
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