dr Dariusz Grech

Detrended Fluctuation Analysis (DFA) and Random Matrix (RM) approach in detection of signals immerse

Econophysics appearance more than a decade ago raised new hope to understand better the existing technologies used in complex systems and to construct basically new ideas in complexity. It is because the financial market is often considered as the largest and most complicated complex system ever built by human. Indeed, a junction between physics and econophysics has become very fruitful. It produced many new approaches describing complexity and significantly modified the existing ones giving a positive feed-back with physics. Detrendisation techniques and random matrices are well written into them. First, I will focus my lecture on the general outlook of DFA and RM techniques applied in science so far. Then, we shall consider their interesting modifications giving possibility to detect any distortion of long-range dependence from the assumed pattern in time series. In particular, signals immersed in noise can be well detected this way. Application to real physical data coming from existing detector of weak signals (Nautilus gravitational wave experiment) will be presented to show the strength of new methods for signal detection and its treatment.