Variable and Fixed Interval Exponential Smoothing
Javier R. Movellan
TL;DR
This paper explores the properties of exponential smoothers for time series data observed at both constant and variable intervals, highlighting their practicality and efficiency in computing running averages.
Contribution
It introduces and characterizes the practical properties of exponential smoothers for irregularly spaced time series data.
Findings
Effective for constant interval data
Adaptable to variable interval signals
Memory-efficient smoothing method
Abstract
Exponential smoothers are a simple and memory efficient way to compute running averages of time series. Here we define and describe practical properties of exponential smoothers for signals observed at constant and variable intervals.
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Taxonomy
TopicsControl Systems and Identification · Probabilistic and Robust Engineering Design · Model Reduction and Neural Networks