TY - GEN
T1 - Fraction-of- Time Density Estimation Based on Linear Interpolation of Time Series
AU - Shevgunov, Timofey
AU - Napolitano, Antonio
N1 - KAUST Repository Item: Exported on 2022-07-01
Acknowledged KAUST grant number(s): OSR-2019-CRG8-4057
Acknowledgements: The study was supported by state assignment of the Ministry of Science and Higher Education of the Russian Federation, research projects No. FSFF-2020-0015, and by the King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research (OSR) under Award OSR-2019-CRG8-4057.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.
PY - 2021/5/7
Y1 - 2021/5/7
N2 - A new estimator for the probability density function of a signal observed over a finite observation interval is proposed. The estimator linearly interpolates adjacent samples and accommodates the presence of probability masses. The analysis is carried out in the fraction-of-time (FOT) probability framework where signals are modeled as single functions of time rather than sample paths of a stochastic process. Numerical results show the better performance of the proposed estimator with respect to the kernel-based estimator. Moreover, the usefulness of analyzing signals in the FOT framework is enlightened.
AB - A new estimator for the probability density function of a signal observed over a finite observation interval is proposed. The estimator linearly interpolates adjacent samples and accommodates the presence of probability masses. The analysis is carried out in the fraction-of-time (FOT) probability framework where signals are modeled as single functions of time rather than sample paths of a stochastic process. Numerical results show the better performance of the proposed estimator with respect to the kernel-based estimator. Moreover, the usefulness of analyzing signals in the FOT framework is enlightened.
UR - http://hdl.handle.net/10754/679546
UR - https://ieeexplore.ieee.org/document/9415991/
UR - http://www.scopus.com/inward/record.url?scp=85105917758&partnerID=8YFLogxK
U2 - 10.1109/IEEECONF51389.2021.9415991
DO - 10.1109/IEEECONF51389.2021.9415991
M3 - Conference contribution
SN - 9780738130897
BT - 2021 Systems of Signals Generating and Processing in the Field of on Board Communications
PB - IEEE
ER -