# Rapid parameter determination of discrete damped sinusoidal oscillations

arXiv: https://arxiv.org/abs/2010.11690 · HTML: https://mlsanity.com/paper/2010.11690/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 9 Oct 2020.

## Built on by (most cited first, 3 of 3)

- [Rapid parameter estimation of discrete decaying signals using autoencoder networks](https://mlsanity.com/paper/2103.08663/) (2021)
- [Autoencoder-Based Parameter Estimation for Superposed Multi-Component Damped Sinusoidal Signals](https://mlsanity.com/paper/2604.03985/) (2026)
- [Parameter Estimation of Ringdown Quasinormal Modes with Autoencoder](https://mlsanity.com/paper/2609.14277/) (2026)

## Abstract (arXiv)

We present different computational approaches for the rapid extraction of the signal parameters of discretely sampled damped sinusoidal signals. We compare time- and frequency-domain-based computational approaches in terms of their accuracy and precision and computational time required in estimating the frequencies of such signals, and observe a general trade-off between precision and speed. Our motivation is precise and rapid analysis of damped sinusoidal signals as these become relevant in view of the recent experimental developments in cavity-enhanced polarimetry and ellipsometry, where the relevant time scales and frequencies are typically within the ~1-10,μs and ~1-100MHz ranges, respectively. In such experimental efforts, single-shot analysis with high accuracy and precision becomes important when developing experiments that study dynamical effects and/or when developing portable instrumentations. Our results suggest that online, running-fashion, microsecond-resolved analysis of polarimetric/ellipsometric measurements with fractional uncertainties at the 10-6 levels, is possible, and using a proof-of-principle experimental demonstration we show that using a frequency-based analysis approach we can monitor and analyze signals at kHz rates and accurately detect signal changes at microsecond time-scales.