1. Theory and algorithm for time series compression
- Creator:
- Svítek, Miroslav
- Format:
- bez média and svazek
- Type:
- model:article and TEXT
- Subject:
- Time series, truncated time series, dimensionality reduction, signal processing, spectral function, Kalman filtering, and LSE parameter estimation
- Language:
- English
- Description:
- The paper presents new methodology how to find and estimate the main features of time series to achieve the reduction of their components (dimensionality reduction) and so to provide the compression of information contained in it under keeping the selected features invariant. The presented compression algorithm is based on estimation of truncated time series components in such a way that the spectrum functions of both original and truncated time series are sufficiently close together. In the end, the set of examples is shown to demonstrate the algorithm performance and to indicate the applications of the presented methodology.
- Rights:
- http://creativecommons.org/publicdomain/mark/1.0/ and policy:public