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Prof. Paolo Paradisi, Istituto di Scienza e Tecnologie dell’Informazione “A. Faedo” (ISTI – CNR), Pisa - Italy - "Multivariate signal processing and complexity analysis in time-varying networks", 8-12 March 2021

20 hours (5 credits)


From remote by using Microsoft Teams. The link will be sent in due time to all students who registered to the seminar.

To register to the course, click here


Short Abstract:
Smart sensors are ubiquitous in nowdays society and will become more and more important in the next future, their applications ranging over many aspects of daily life, such as: (i) healthcare: wearable devices for monitoring of physiological parameters in both hospitals or home (e.g., elderly); (ii) monitoring of athlete's perfomance; (iii) continuous monitoring of industrial plaforms for automatic diagnosis (selfmonitoring) or optimization in the production line (Industry 4.0); (iv) human-computer interfaces; (v) automotive. These sensors often give a continuous time monitoring and, thus, a large dataset of complex signals that need to be processed, both in real time or offline, depending on the specific application. Many
monitoring systems are developed as a wireless sensor network, i.e., a network with a complex topology of the links, where each link is a communication channel between sensors.
Thus, a proper processing of these large datasets of time signals is crucial, not only regarding computational efficiency, but also for the extraction of informative parameters (information retrieval).
This course will cover the basic concepts and techniques used in the processing of complex time signals, also including feature extraction in multivariate signals with particular attention to connectivity features of time-varying networks.
In the first part, we will give an overview of the main results of classical signal processing. Some practical examples will be given during the lectures, in order to make the students more confident with signal processing tools.
In the second part, we will focus on connectivity measures defined on time-varying networks. We will discuss some specific applications, mainly in health applications and physiological monitoring.
Finally, in the third part, we will give a few insights on recent developments in the processing of signals with complex intermittency, showing some applications in the field of neurophysiology.

Course Contents in brief:

  1. Statistical signal processing
  2. Multivariate signals
  3. Time-varying networks
  4. Network connectivity and connectomics
  5. Complex systems
  6. Signals with complex intermittency


  1. lunedì 08 marzo 2021: dalle 9 alle 13
  2. martedì 09 marzo 2021: dalle 9 alle 13
  3. mercoledì 10 marzo 2021: dalle 9 alle 13
  4. giovedì 11 marzo 2021: dalle 9 alle 13
  5. venerdì 12 marzo 2021: dalle 9 alle 13