19,420 research outputs found
The PyCBC search for gravitational waves from compact binary coalescence
We describe the PyCBC search for gravitational waves from compact-object
binary coalescences in advanced gravitational-wave detector data. The search
was used in the first Advanced LIGO observing run and unambiguously identified
two black hole binary mergers, GW150914 and GW151226. At its core, the PyCBC
search performs a matched-filter search for binary merger signals using a bank
of gravitational-wave template waveforms. We provide a complete description of
the search pipeline including the steps used to mitigate the effects of noise
transients in the data, identify candidate events and measure their statistical
significance. The analysis is able to measure false-alarm rates as low as one
per million years, required for confident detection of signals. Using data from
initial LIGO's sixth science run, we show that the new analysis reduces the
background noise in the search, giving a 30% increase in sensitive volume for
binary neutron star systems over previous searches.Comment: 29 pages, 7 figures, accepted by Classical and Quantum Gravit
Systematic approach to nonlinear filtering associated with aggregation operators. Part 2. Frechet MIMO-filters
Median filtering has been widely used in scalar-valued image processing as an edge preserving operation. The basic idea is that the pixel value is replaced by the median of the pixels contained in a window around it. In this work, this idea is extended onto vector-valued images. It is based on the fact that the median is also the value that minimizes the sum of distances between all grey-level pixels in the window. The Frechet median of a discrete set of vector-valued pixels in a metric space with a metric is the point minimizing the sum of metric distances to the all sample pixels. In this paper, we extend the notion of the Frechet median to the general Frechet median, which minimizes the Frechet cost function (FCF) in the form of aggregation function of metric distances, instead of the ordinary sum. Moreover, we propose use an aggregation distance instead of classical metric distance. We use generalized Frechet median for constructing new nonlinear Frechet MIMO-filters for multispectral image processing. (C) 2017 The Authors. Published by Elsevier Ltd.This work was supported by grants the RFBR No 17-07-00886, No 17-29-03369 and by Ural State Forest University Engineering's Center of Excellence in "Quantum and Classical Information Technologies for Remote Sensing Systems"
A low-cost time-hopping impulse radio system for high data rate transmission
We present an efficient, low-cost implementation of time-hopping impulse
radio that fulfills the spectral mask mandated by the FCC and is suitable for
high-data-rate, short-range communications. Key features are: (i) all-baseband
implementation that obviates the need for passband components, (ii) symbol-rate
(not chip rate) sampling, A/D conversion, and digital signal processing, (iii)
fast acquisition due to novel search algorithms, (iv) spectral shaping that can
be adapted to accommodate different spectrum regulations and interference
environments. Computer simulations show that this system can provide 110Mbit/s
at 7-10m distance, as well as higher data rates at shorter distances under FCC
emissions limits. Due to the spreading concept of time-hopping impulse radio,
the system can sustain multiple simultaneous users, and can suppress narrowband
interference effectively.Comment: To appear in EURASIP Journal on Applied Signal Processing (Special
Issue on UWB - State of the Art
Toward Early-Warning Detection of Gravitational Waves from Compact Binary Coalescence
Rapid detection of compact binary coalescence (CBC) with a network of
advanced gravitational-wave detectors will offer a unique opportunity for
multi-messenger astronomy. Prompt detection alerts for the astronomical
community might make it possible to observe the onset of electromagnetic
emission from (CBC). We demonstrate a computationally practical filtering
strategy that could produce early-warning triggers before gravitational
radiation from the final merger has arrived at the detectors.Comment: 16 pages, 7 figures, published in ApJ. Reformatted preprint with
emulateap
Consensus image method for unknown noise removal
Noise removal has been, and it is nowadays, an important task in computer vision. Usually, it is a previous task preceding other tasks, as segmentation or reconstruction. However, for most existing denoising algorithms the noise model has to be known in advance. In this paper, we introduce a new approach based on consensus to deal with unknown noise models. To do this, different filtered images are obtained, then combined using multifuzzy sets and averaging aggregation functions. The final decision is made by using a penalty function to deliver the compromised image. Results show that this approach is consistent and provides a good compromise between filters.This work is supported by the European Commission under Contract No. 238819 (MIBISOC Marie Curie ITN). H. Bustince was supported by Project TIN 2010-15055 of the Spanish Ministry of Science
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