69421 - ELECTRONIC SYSTEMS SIGNAL PROCESSING M

Academic Year 2018/2019

  • Moduli: Riccardo Rovatti (Modulo 1) Mauro Mangia (Modulo 2)
  • Teaching Mode: Traditional lectures (Modulo 1) Traditional lectures (Modulo 2)
  • Campus: Bologna
  • Corso: Second cycle degree programme (LM) in Electronic Engineering (cod. 0934)

Learning outcomes

The student will learn the basic mathematical tools to analyze and design systems that process information-bearing signals form their acquisition, to processing, trasmission, compression and storage by means of electronic systems.

Course contents

Revision of basic probability theory. Characterization of stochastic processes by joint probabilities, correlations, and projections. Stationary random processes, ergodicity, mixing, exactness. Transformations of random vectors with a finite number of counterimages. Linear transformations of random vectors. Quantization. Linear filters: effects on correlations. Linear filters: characterization by projections, SVD-like decomposition. Linear filters: the ideal low-pass case and the relationship between time-limiting and band-limiting. Gaussian variables, vectors and processes. Power spectrum. Wiener-Kinchine theorem. Basics of estimation theory: bias and consistency. Periodogram and modified periodogram. Minimum variance spectral estimation. Linear prediction: orthogonality principle and Yule-Walker equations. Whitener filter and predictable processes. Paley-Wiener conditions and regular processes. Wold's decomposition theorem. Maximum-entropy spectral estimation. Finite-memory processes. Discrete-time, memory-1, stationary processes as Markov chains. Finite Markov chains: transition matrix and its properties.

Assessment methods

Oral examination.

Office hours

See the website of Riccardo Rovatti

See the website of Mauro Mangia