Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userSpectral Kurtosis Statistics of Transient Signals
257
0
0.0
(
0
)
Authors
Gelu M. Nita
Ask ChatGPT about the research
No Arabic abstract
We obtain analytical approximations for the expectation and variance of the Spectral Kurtosis estimator in the case of Gaussian and coherent transient time domain signals mixed with a quasi-stationary Gaussian background, which are suitable for practical estimations of their signal-to-noise ratio and duty-cycle relative to the instrumental integration time. We validate these analytical approximations by means of numerical simulations and demonstrate that such estimates are affected by statistical uncertainties that, for a suitable choice of the integration time, may not exceed a few percent. Based on these analytical results, we suggest a multiscale Spectral Kurtosis spectrometer design optimized for real-time detection of transient signals, automatic discrimination based on their statistical signature, and measurement of their properties.
rate research
Read More
We describe in general terms the practical use in astronomy of a higher-order statistical quantity called Spectral Kurtosis (SK), and describe the first implementation of SK-enabled firmware in the F-engine (Fourier transform-engine) of a digital FX correlator for Expanded Owens Valley Solar Array (EOVSA). The development of the theory for SK is summarized, leading to an expression for generalized SK that is applicable to both SK spectrometers and those not specifically designed for SK. We also give the means for computing both the SK estimator and thresholds for its application as a discriminator of RFI contamination. Tests of the performance of EOVSA as an SK spectrometer are shown to agree precisely with theoretical expectations, and the methods for configuring the correlator for correct SK operation are described.
Due to its conceptual simplicity and its proven effectiveness in real-time detection and removal of radio frequency interference (RFI) from radio astronomy data, the Spectral Kurtosis (SK) estimator is likely to become a standard tool of a new generation of radio telescopes. However, the SK estimator in its original form must be developed from instantaneous power spectral density (PSD) estimates, and hence cannot be employed as an RFI excision tool downstream of the data pipeline in existing instruments where any time averaging is performed. In this letter, we develop a generalized estimator with wider applicability for both instantaneous and averaged spectral data, which extends its practical use to a much larger pool of radio instruments.
Time domain astronomy has come of age with astronomers now able to monitor the sky at high cadence both across the electromagnetic spectrum and using neutrinos and gravitational waves. The advent of new observing facilities permits new science, but the ever increasing throughput of facilities demands efficient communication of coincident detections and better subsequent coordination among the scientific community so as to turn detections into scientific discoveries. To discuss the revolution occurring in our ability to monitor the Universe and the challenges it brings, on 2012 April 25-26 a group of scientists from observational and theoretical teams studying transients met with representatives of the major international transient observing facilities at the Kavli Royal Society International Centre, UK. This immediately followed the Royal Society Discussion meeting New windows on transients across the Universe held in London. Here we present a summary of the Kavli meeting at which the participants discussed the science goals common to the transient astronomy community and analysed how to better meet the challenges ahead as ever more powerful observational facilities come on stream.
Given a random text over a finite alphabet, we study the frequencies at which fixed-length words occur as subsequences. As the data size grows, the joint distribution of word counts exhibits a rich asymptotic structure. We investigate all linear combinations of subword statistics, and fully characterize their different orders of magnitude using diverse algebraic tools. Moreover, we establish the spectral decomposition of the space of word statistics of each order. We provide explicit formulas for the eigenvectors and eigenvalues of the covariance matrix of the multivariate distribution of these statistics. Our techniques include and elaborate on a set of algebraic word operators, recently studied and employed by Dieker and Saliola (Adv Math, 2018). Subword counts find applications in Combinatorics, Statistics, and Computer Science. We revisit special cases from the combinatorial literature, such as intransitive dice, random core partitions, and questions on random walk. Our structural approach describes in a unified framework several classical statistical tests. We propose further potential applications to data analysis and machine learning.
The professional literature provides one means to review the evolution and geographic distribution of the scientific communities engaged in solar and heliospheric physics. With help of the Astrophysics Data System (NASA/ADS), I trace the growth of the research community over the past century from a few dozen researchers early in the 20-th Century to over 4,000 names with over refereed 2,000 publications in recent years, with 90% originating from 20 countries, being published in 90 distinct journals. Overall, the lead authors of these publications have their affiliations for 45% in Europe, 29% in the Americas, 24% in Australasia, and 2% in Africa and Arab countries. Publications most frequently appear (in decreasing order) in the Astrophysical Journal, the Journal of Geophysical Research (Space Physics), Solar Physics, Astronomy and Astrophysics, and Advances in Space Research (adding up to 59% of all publications in 2015).
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
