Acquisition of basic theoretical knowledge of signal theory, including the definition of a signal, its representation in the time and frequency domains, and the Fourier transform; knowledge of signal sampling and quantisation techniques, and the related issues of aliasing and noise; theoretical knowledge of fundamental notions of probability theory and random processes, for the representation of signals as their realisations; enabling the student to analyse and process biomedical signals using the signal theory methodologies.
Curriculum
teacher profile teaching materials
Axiomatic theory of probability. The axioms of probability. Bayes' theorem. Random variables. Distribution and probability density function. Mean, variance, moments, covariance matrix. Characteristic function. Functions of one random variable. Multiple random variables: joint distributions. Conditional distributions. Central limit theorem. Gaussian random variables: univariate and multivariate. Bernoulli random variable. Poisson random variable. Laws of large numbers. Stochastic processes: general concepts. Stationary processes. Ergodic processes and related theorems. Parametric stochastic processes. Linear and non-linear transformation of stochastic ergodic processes. Continuous-time random processes; gaussian process, armonic process.
L. Piazzo - Teoria dei Segnali
Programme
Definition of signal. Signal representations. The signals as elements of a vectorial space. Generalized Fourier Representation. Cross and auto-correlation function: definition and properties. Linear transformations. Linear and time-invariant systems. I/O relations: convolution integral and its properties. Fourier series expansion. Fourier Transform. Parseval and Wiener theorems. Energy and power spectral density. Limited bandwidth signals. Sampling theorem. Sub-sampling effects. Hilbert transform. Analytical signal, complex envelope and low-frequency components of a band-pass signal. Bandwidth limited signals linear transformations and their samples relations.Axiomatic theory of probability. The axioms of probability. Bayes' theorem. Random variables. Distribution and probability density function. Mean, variance, moments, covariance matrix. Characteristic function. Functions of one random variable. Multiple random variables: joint distributions. Conditional distributions. Central limit theorem. Gaussian random variables: univariate and multivariate. Bernoulli random variable. Poisson random variable. Laws of large numbers. Stochastic processes: general concepts. Stationary processes. Ergodic processes and related theorems. Parametric stochastic processes. Linear and non-linear transformation of stochastic ergodic processes. Continuous-time random processes; gaussian process, armonic process.
Core Documentation
R. Cusani - Teoria dei SegnaliL. Piazzo - Teoria dei Segnali
Reference Bibliography
R. Cusani- Teoria dei Segnali- Ingegneria DuemilaAttendance
Attending lectures is not mandatory yet strongly encouragedType of evaluation
Exams with written and oral evaluations teacher profile teaching materials
Axiomatic theory of probability. The axioms of probability. Bayes' theorem. Random variables. Distribution and probability density function. Mean, variance, moments, covariance matrix. Characteristic function. Functions of one random variable. Multiple random variables: joint distributions. Conditional distributions. Central limit theorem. Gaussian random variables: univariate and multivariate. Bernoulli random variable. Poisson random variable. Laws of large numbers. Stochastic processes: general concepts. Stationary processes. Ergodic processes and related theorems. Parametric stochastic processes. Linear and non-linear transformation of stochastic ergodic processes. Continuous-time random processes; gaussian process, armonic process.
L. Piazzo - Teoria dei Segnali
Programme
Definition of signal. Signal representations. The signals as elements of a vectorial space. Generalized Fourier Representation. Cross and auto-correlation function: definition and properties. Linear transformations. Linear and time-invariant systems. I/O relations: convolution integral and its properties. Fourier series expansion. Fourier Transform. Parseval and Wiener theorems. Energy and power spectral density. Limited bandwidth signals. Sampling theorem. Sub-sampling effects. Hilbert transform. Analytical signal, complex envelope and low-frequency components of a band-pass signal. Bandwidth limited signals linear transformations and their samples relations.Axiomatic theory of probability. The axioms of probability. Bayes' theorem. Random variables. Distribution and probability density function. Mean, variance, moments, covariance matrix. Characteristic function. Functions of one random variable. Multiple random variables: joint distributions. Conditional distributions. Central limit theorem. Gaussian random variables: univariate and multivariate. Bernoulli random variable. Poisson random variable. Laws of large numbers. Stochastic processes: general concepts. Stationary processes. Ergodic processes and related theorems. Parametric stochastic processes. Linear and non-linear transformation of stochastic ergodic processes. Continuous-time random processes; gaussian process, armonic process.
Core Documentation
R. Cusani - Teoria dei SegnaliL. Piazzo - Teoria dei Segnali
Reference Bibliography
R. Cusani- Teoria dei Segnali- Ingegneria DuemilaAttendance
Attending lectures is not mandatory yet strongly encouragedType of evaluation
Exams with written and oral evaluations