In this paper, we estimate the time-varying COVID-19 contact rate of a Susceptible-Infected-Recovered (SIR) model. Our measurement of the contact rate is constructed using data on actively infected, recovered and deceased cases. We propose a new trend filtering method that is a variant of the...

In this paper, we estimate the time-varying COVID-19 contact rate of a Susceptible-Infected-Recovered (SIR) model. Our measurement of the contact rate is constructed using data on actively infected, recovered and deceased cases. We propose a new trend filtering method that is a variant of the...

The features extraction is the main step in a Brain-Computer Interface (BCI) design. Its goal is to create features easy to be interpreted in order to produce the most accurate control commands. For this end, these features must include all the original signal characteristics. The generated...

Signal enhancement is useful in many areas like social, medicine and engineering. It can be utilized in data mining approach for social and security aspects. Signal decomposition method is an alternative choice due to the elimination of noise and signal enhancement. In this paper, two different...

We introduce a multistep-ahead forecasting methodology that combines empirical mode decomposition (EMD) and support vector regression (SVR). This methodology is based on the idea that the forecasting task is simplified by using as input for SVR the time series decomposed with EMD. The outcomes...

In this paper, the dynamics of Standard and Poor's 500 (S&P 500) stock price index is analysed within a time-frequency framework over a monthly period 1791:08-2015:05. Using the Empirical Mode Decomposition technique, the S&P 500 stock price index is divided into different frequencies known as...