# The effect of dead time on randomly sampled power spectral estimates

## TL;DR

This paper analyzes how finite sampling time and dead time in measurement systems affect the accuracy of power spectral estimates of stationary stochastic signals, extending previous models to more realistic scenarios.

## Contribution

It introduces a method to account for finite dead time effects in power spectral estimation, improving the accuracy of spectral analysis in real measurement systems.

## Key findings

- Finite dead time distorts power spectral estimates.
- Finite sampling time impacts spectral measurement accuracy.
- Extended models better match real measurement system behavior.

## Abstract

We investigate power spectra of a randomly sampled stationary stochastic signal, e.g. a spatial component of a turbulent velocity. We extend the methods of previous authors that basically assumed point or delta function sampling by including features characteristic of real measurement systems. We consider both the effect on the measured spectrum of a finite sampling time, i.e., a finite time during which the signal is acquired, and a finite dead time, that is a time in which the signal processor is busy evaluating a data point and therefore unable to measure a subsequent data point arriving within the dead time delay.