Fraction-of- Time Density Estimation Based on Linear Interpolation of Time Series

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 fr...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:2021 Systems of Signals Generating and Processing in the Field of on Board Communications S. 1 - 4
Hauptverfasser: Shevgunov, Timofey, Napolitano, Antonio
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 16.03.2021
Schlagworte:
Analytical models
cyclostationary processes
Density measurement
Estimation
fraction-of-time probability
Interpolation
probability density estimator
Probability density function
Stochastic processes
Time series analysis
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung: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.
DOI:10.1109/IEEECONF51389.2021.9415991