One classical problem in many applied fields of research, like Geophysics, Medicine, Engineering, Economy, and Finance, is, given a signal, how to extract hidden information and features contained in it, like, for instance, quasi periodicities, trends, or hidden frequencies. 

Standard methods like Fourier and Wavelet Transform, historically used in signal processing, proved to be limited when nonstationary phenomena are present. For this reason in the last two decades, several new nonlinear methods have been developed by many research groups around the world and they have been used extensively in the applications. 

In this talk, we will review some of these techniques, and detail Iterative Filtering and its generalizations. We will discuss the theoretical and numerical properties of these methods and show their limitations. A few applications to real-life signals will be presented and we will conclude by reviewing some of the interesting open problems in this research direction.  

https://univienna.zoom.us/j/64895816787?pwd=L0tHVnBPUkJFQVVSR3Y2QnhVRXRGZz09