The main research topic within the NSE laboratory is the study of signals produced by non-linear dynamical systems. Examples of problems addressed in the lab are the identification of optimal embedding parameters for sequences generated by chaotic systems, new methods for the estimation of invariant quantities such as the correlation dimension and the Lyapunov Maximum Exponent, and the separation of the noisy component from the deterministic component within a signal. These objectives are pursued both through mathematical and statistical tools, and by performing intensive numerical calculations applied to experimentally measured or synthetically generated signals.
A substantial part of the research activity concerns the investigation of physical problems by means of methods based on Information Theory, and therefore on the concept of entropy. These methods are a complementary approach to more conventional and established analytical techniques. Fields of application include neuroscience, geophysics, climatology and econophysics.
The development of advanced electronics, both analog and digital, is the most relevant technical expertise within the NSE laboratory.

Research activities

Core goals of the research carried out within the NSE Lab are the development of new methods and algorithms for the investigation of signals produced by nonlinear dynamical systems. Examples of issues tackled in the lab are the assessment of optimal embedding parameters for sequences generated by chaotic systems, new ways for estimating invariant quantities such as correlation dimension and Maximum Lyapunov Exponent, and the disentanglement of the noisy component from the deterministic one in a time series. These goals are pursued both through mathematical and statistical tools and by carrying out intensive numerical computations applied to experimentally-recorded and synthetic signals.
An increasing part of the research is devoted to addressing physical problems with information-theoretical – i.e. entropy-based – methods, which provide a complementary approach to more conventional and established analytical techniques.
Another main research line of the laboratory is the study of multivariate, experimentally-recorded time series produced by complex systems. For example, the investigation of signals produced by the human brain makes up an issue that requires powerful nonlinear techniques to unveil brain functions, assess the existence of network structures, and characterize these functions and networks. Within this context, we are keen to investigate the role of noise within the human brain. To this goal, advanced statistical methods are applied to multivariate time series sampled via magnetoencephalography (MEG) and electroencephalography (EEG). Part of the research is carried out within the Center for Mind/Brain Sciences (CIMeC) of the University of Trento. Possible additional fields of application of these techniques are climate research and economics.
Finally, the development of advanced analog and digital electronics is possibly the main technical expertise present in the lab.

Group members