6,806 research outputs found
TFAW: wavelet-based signal reconstruction to reduce photometric noise in time-domain surveys
There have been many efforts to correct systematic effects in astronomical
light curves to improve the detection and characterization of planetary
transits and astrophysical variability. Algorithms like the Trend Filtering
Algorithm (TFA) use simultaneously-observed stars to remove systematic effects,
and binning is used to reduce high-frequency random noise. We present TFAW, a
wavelet-based modified version of TFA. TFAW aims to increase the periodic
signal detection and to return a detrended and denoised signal without
modifying its intrinsic characteristics. We modify TFA's frequency analysis
step adding a Stationary Wavelet Transform filter to perform an initial noise
and outlier removal and increase the detection of variable signals. A wavelet
filter is added to TFA's signal reconstruction to perform an adaptive
characterization of the noise- and trend-free signal and the noise contribution
at each iteration while preserving astrophysical signals. We carried out tests
over simulated sinusoidal and transit-like signals to assess the effectiveness
of the method and applied TFAW to real light curves from TFRM. We also studied
TFAW's application to simulated multiperiodic signals, improving their
characterization. TFAW improves the signal detection rate by increasing the
signal detection efficiency (SDE) up to a factor ~2.5x for low SNR light
curves. For simulated transits, the transit detection rate improves by a factor
~2-5x in the low-SNR regime compared to TFA. TFAW signal approximation performs
up to a factor ~2x better than bin averaging for planetary transits. The
standard deviations of simulated and real TFAW light curves are ~40x better
than TFA. TFAW yields better MCMC posterior distributions and returns lower
uncertainties, less biased transit parameters and narrower (~10x) credibility
intervals for simulated transits. We present a newly-discovered variable star
from TFRM.Comment: Accepted for publication by A&A. 13 pages, 16 figures and 5 table
Spectral analysis for nonstationary audio
A new approach for the analysis of nonstationary signals is proposed, with a
focus on audio applications. Following earlier contributions, nonstationarity
is modeled via stationarity-breaking operators acting on Gaussian stationary
random signals. The focus is on time warping and amplitude modulation, and an
approximate maximum-likelihood approach based on suitable approximations in the
wavelet transform domain is developed. This paper provides theoretical analysis
of the approximations, and introduces JEFAS, a corresponding estimation
algorithm. The latter is tested and validated on synthetic as well as real
audio signal.Comment: IEEE/ACM Transactions on Audio, Speech and Language Processing,
Institute of Electrical and Electronics Engineers, In pres
Characterization of the near-Earth Asteroid 2002NY40
In August 2002, the near-Earth asteroid 2002 NY40, made its closest approach
to the Earth. This provided an opportunity to study a near-Earth asteroid with
a variety of instruments. Several of the telescopes at the Maui Space
Surveillance System were trained at the asteroid and collected adaptive optics
images, photometry and spectroscopy. Analysis of the imagery reveals the
asteroid is triangular shaped with significant self-shadowing. The photometry
reveals a 20-hour period and the spectroscopy shows that the asteroid is a
Q-type
Stepwise Iterative Fourier Transform: The SIFT
A program, designed specifically to study the respective effects of some common data problems on results obtained through stepwise iterative Fourier transformation of synthetic data with known waveform composition, was outlined. Included in this group were the problems of gaps in the data, different time-series lengths, periodic but nonsinusoidal waveforms, and noisy (low signal-to-noise) data. Results on sinusoidal data were also compared with results obtained on narrow band noise with similar characteristics. The findings showed that the analytic procedure under study can reliably reduce data in the nature of (1) sinusoids in noise, (2) asymmetric but periodic waves in noise, and (3) sinusoids in noise with substantial gaps in the data. The program was also able to analyze narrow-band noise well, but with increased interpretational problems. The procedure was shown to be a powerful technique for analysis of periodicities, in comparison with classical spectrum analysis techniques. However, informed use of the stepwise procedure nevertheless requires some background of knowledge concerning characteristics of the biological processes under study
Comparison of different repetitive control architectures: synthesis and comparison. Application to VSI Converters
Repetitive control is one of the most used control approaches to deal with periodic references/disturbances. It owes its properties to the inclusion of an internal model in the controller that corresponds to a periodic signal generator. However, there exist many different ways to include this internal model. This work presents a description of the different schemes by means of which repetitive control can be implemented. A complete analytic analysis and comparison is performed together with controller synthesis guidance. The voltage source inverter controller experimental results are included to illustrative conceptual developmentsPeer ReviewedPostprint (published version
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