176,229 research outputs found
On Norm-Based Estimations for Domains of Attraction in Nonlinear Time-Delay Systems
For nonlinear time-delay systems, domains of attraction are rarely studied
despite their importance for technological applications. The present paper
provides methodological hints for the determination of an upper bound on the
radius of attraction by numerical means. Thereby, the respective Banach space
for initial functions has to be selected and primary initial functions have to
be chosen. The latter are used in time-forward simulations to determine a first
upper bound on the radius of attraction. Thereafter, this upper bound is
refined by secondary initial functions, which result a posteriori from the
preceding simulations. Additionally, a bifurcation analysis should be
undertaken. This analysis results in a possible improvement of the previous
estimation. An example of a time-delayed swing equation demonstrates the
various aspects.Comment: 33 pages, 8 figures, "This is a pre-print of an article published in
'Nonlinear Dynamics'. The final authenticated version is available online at
https://doi.org/10.1007/s11071-020-05620-8
Nonanticipating estimation applied to sequential analysis and changepoint detection
Suppose a process yields independent observations whose distributions belong
to a family parameterized by \theta\in\Theta. When the process is in control,
the observations are i.i.d. with a known parameter value \theta_0. When the
process is out of control, the parameter changes. We apply an idea of Robbins
and Siegmund [Proc. Sixth Berkeley Symp. Math. Statist. Probab. 4 (1972) 37-41]
to construct a class of sequential tests and detection schemes whereby the
unknown post-change parameters are estimated. This approach is especially
useful in situations where the parametric space is intricate and mixture-type
rules are operationally or conceptually difficult to formulate. We exemplify
our approach by applying it to the problem of detecting a change in the shape
parameter of a Gamma distribution, in both a univariate and a multivariate
setting.Comment: Published at http://dx.doi.org/10.1214/009053605000000183 in the
Annals of Statistics (http://www.imstat.org/aos/) by the Institute of
Mathematical Statistics (http://www.imstat.org
Multi-Level Pre-Correlation RFI Flagging for Real-Time Implementation on UniBoard
Because of the denser active use of the spectrum, and because of radio
telescopes higher sensitivity, radio frequency interference (RFI) mitigation
has become a sensitive topic for current and future radio telescope designs.
Even if quite sophisticated approaches have been proposed in the recent years,
the majority of RFI mitigation operational procedures are based on
post-correlation corrupted data flagging. Moreover, given the huge amount of
data delivered by current and next generation radio telescopes, all these RFI
detection procedures have to be at least automatic and, if possible, real-time.
In this paper, the implementation of a real-time pre-correlation RFI
detection and flagging procedure into generic high-performance computing
platforms based on Field Programmable Gate Arrays (FPGA) is described,
simulated and tested. One of these boards, UniBoard, developed under a Joint
Research Activity in the RadioNet FP7 European programme is based on eight
FPGAs interconnected by a high speed transceiver mesh. It provides up to ~4
TMACs with Altera Stratix IV FPGA and 160 Gbps data rate for the input data
stream.
Considering the high in-out data rate in the pre-correlation stages, only
real-time and go-through detectors (i.e. no iterative processing) can be
implemented. In this paper, a real-time and adaptive detection scheme is
described.
An ongoing case study has been set up with the Electronic Multi-Beam Radio
Astronomy Concept (EMBRACE) radio telescope facility at Nan\c{c}ay Observatory.
The objective is to evaluate the performances of this concept in term of
hardware complexity, detection efficiency and additional RFI metadata rate
cost. The UniBoard implementation scheme is described.Comment: 16 pages, 13 figure
An improved method for estimating the neutron background in measurements of neutron capture reactions
The relation between the neutron background in neutron capture measurements
and the neutron sensitivity related to the experimental setup is examined. It
is pointed out that a proper estimate of the neutron background may only be
obtained by means of dedicated simulations taking into account the full
framework of the neutron-induced reactions and their complete temporal
evolution. No other presently available method seems to provide reliable
results, in particular under the capture resonances. An improved neutron
background estimation technique is proposed, the main improvement regarding the
treatment of the neutron sensitivity, taking into account the temporal
evolution of the neutron-induced reactions. The technique is complemented by an
advanced data analysis procedure based on relativistic kinematics of neutron
scattering. The analysis procedure allows for the calculation of the neutron
background in capture measurements, without requiring the time-consuming
simulations to be adapted to each particular sample. A suggestion is made on
how to improve the neutron background estimates if neutron background
simulations are not available.Comment: 11 pages, 9 figure
Integration of Satellites in 5G through LEO Constellations
The standardization of 5G systems is entering in its critical phase, with
3GPP that will publish the PHY standard by June 2017. In order to meet the
demanding 5G requirements both in terms of large throughput and global
connectivity, Satellite Communications provide a valuable resource to extend
and complement terrestrial networks. In this context, we consider a
heterogeneous architecture in which a LEO mega-constellation satellite system
provides backhaul connectivity to terrestrial 5G Relay Nodes, which create an
on-ground 5G network. Since large delays and Doppler shifts related to
satellite channels pose severe challenges to terrestrial-based systems, in this
paper we assess their impact on the future 5G PHY and MAC layer procedures. In
addition, solutions are proposed for Random Access, waveform numerology, and
HARQ procedures.Comment: Submitted to IEEE Global Communications Conference (GLOBECOM) 201
Intersection SPaT Estimation by means of Single-Source Connected Vehicle Data
The file attached to this record is the author's final peer reviewed version.Current traffic management systems in urban networks require real-time estimation of the traffic states. With the development of in-vehicle and communication technologies, connected vehicle data has emerged as a new data source for traffic measurement and estimation. In this work, a machine learning-based methodology for signal phase and timing information (SPaT) which is highly valuable for many applications such as green light optimal advisory systems and real-time vehicle navigation is proposed. The proposed methodology utilizes data from connected vehicles travelling within urban signalized links to estimate the queue tail location, vehicle accumulation, and subsequently, link outflow. Based on the produced high-resolution outflow estimates and data from crossing connected vehicles, SPaT information is estimated via correlation analysis and a machine learning approach. The main contribution is that the single-source proposed approach relies merely on connected vehicle data and requires neither prior information such as intersection cycle time nor data from other sources such as conventional traffic measuring tools. A sample four-leg intersection where each link comprises different number of lanes and experiences different traffic condition is considered as a testbed. The validation of the developed approach has been undertaken by comparing the produced estimates with realistic micro-simulation results as ground truth, and the achieved simulation results are promising even at low penetration rates of connected vehicles
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