Prof. M. Biagi

Semester II

6 credits

Info (classes, topics, textbook....)

The course aims at giving instruments to understand the role of information and its representation. How this information should be acquired, the istruments used as well as, the possible compression methods will be a focus of this course. More, passing from theory to practice, some specific problems of data monitoring related to vehicles and pollution will be presented by showing also the impact of array processing. Last, some methods for transferring information will be highlighted.

  1. Introduction (Historical notes, the role of information and monitoring, communication vs. information)

  2. Sensors (Transducers, Active sensors, Passive sensors)

  3. Information Measurement (sampling: undersampling, oversampling, compressive sensing, spectral analysis and estimation, information theory and reliability theory, quantum information theory and quantum calculus, lossy and lossless coding)

  4. Data Monitoring: (Underwater environment monitoring (experiences in Lab available), Air pollution monitoring, Vehicle traffic analysis via smart lighting systems, Diversity techniques )

  5. Data Analysis and communications:  quantum computers essentials, Intelligent Transportation systems, Underwater Acoustic Communications (experiences in Lab available),  Visible Light Communications, Array processing.