7,928 research outputs found
CMB map restoration
Estimating the cosmological microwave background is of utmost importance for
cosmology. However, its estimation from full-sky surveys such as WMAP or more
recently Planck is challenging: CMB maps are generally estimated via the
application of some source separation techniques which never prevent the final
map from being contaminated with noise and foreground residuals. These spurious
contaminations whether noise or foreground residuals are well-known to be a
plague for most cosmologically relevant tests or evaluations; this includes CMB
lensing reconstruction or non-Gaussian signatures search. Noise reduction is
generally performed by applying a simple Wiener filter in spherical harmonics;
however this does not account for the non-stationarity of the noise. Foreground
contamination is usually tackled by masking the most intense residuals detected
in the map, which makes CMB evaluation harder to perform. In this paper, we
introduce a novel noise reduction framework coined LIW-Filtering for Linear
Iterative Wavelet Filtering which is able to account for the noise spatial
variability thanks to a wavelet-based modeling while keeping the highly desired
linearity of the Wiener filter. We further show that the same filtering
technique can effectively perform foreground contamination reduction thus
providing a globally cleaner CMB map. Numerical results on simulated but
realistic Planck data are provided
Software Defined Radio Implementation of Carrier and Timing Synchronization for Distributed Arrays
The communication range of wireless networks can be greatly improved by using
distributed beamforming from a set of independent radio nodes. One of the key
challenges in establishing a beamformed communication link from separate radios
is achieving carrier frequency and sample timing synchronization. This paper
describes an implementation that addresses both carrier frequency and sample
timing synchronization simultaneously using RF signaling between designated
master and slave nodes. By using a pilot signal transmitted by the master node,
each slave estimates and tracks the frequency and timing offset and digitally
compensates for them. A real-time implementation of the proposed system was
developed in GNU Radio and tested with Ettus USRP N210 software defined radios.
The measurements show that the distributed array can reach a residual frequency
error of 5 Hz and a residual timing offset of 1/16 the sample duration for 70
percent of the time. This performance enables distributed beamforming for range
extension applications.Comment: Submitted to 2019 IEEE Aerospace Conferenc
EMD-based filtering (EMDF) of low-frequency noise for speech enhancement
An Empirical Mode Decomposition based filtering (EMDF) approach is presented as a post-processing stage for speech enhancement. This method is particularly effective in low frequency noise environments. Unlike previous EMD based denoising methods, this approach does not make the assumption that the contaminating noise signal is fractional Gaussian Noise. An adaptive method is developed to select the IMF index for separating the noise components from the speech based on the second-order IMF statistics. The low frequency noise components are then separated by a partial reconstruction from the IMFs. It is shown that the proposed EMDF technique is able to suppress residual noise from speech signals that were enhanced by the conventional optimallymodified log-spectral amplitude approach which uses a minimum statistics based noise estimate. A comparative performance study is included that demonstrates the effectiveness of the EMDF system in various noise environments, such as car interior noise, military vehicle noise and babble noise. In particular, improvements up to 10 dB are obtained in car noise environments. Listening tests were performed that confirm the results
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