Many systems are monitored and evaluated for their behavior using time signals. Additional
information about the properties of a time signal can be obtained by representing the time …

This paper describes the application of the adaptive whitening filter and the wavelet
transform used to detect the abrupt changes in the signals recorded during disturbances in …

Extracting the underlying trend signal is a crucial step to facilitate time series analysis like
forecasting and anomaly detection. Besides noise signal, time series can contain not only …

This paper investigates multiscale interdependence between the stock markets of Germany,
Austria, France, and the United Kingdom. Wavelet energy additive decomposition was …

Monthly precipitation extremes from gauging stations across Germany were studied using
continuous wavelet tools toward variance and frequency‐time localization and detection of …

Forecasting the returns of assets at high frequency is the key challenge for high-frequency
algorithmic trading strategies. In this paper, we propose a jump-diffusion model for asset …

This paper describes the application of the abrupt change detection technologies to detect
the abrupt changes in the signals recorded during disturbances in the electrical power …

The paper examines the comovement and spillover dynamics between the returns of the
Czech and some major European stock markets (namely, the Austrian, French, German, and …

This paper studies comovement between changes in sovereign bond yields and stock
market returns for ten Eurozone countries (Austria, Belgium, Finland, France, Ireland, Italy …

Temperature variability in the Czech Republic is analysed by means of wavelet transforms.
This advanced time–frequency analysis provides information about the nature and time …