Syllabus of the course:
SYSTEM IDENTIFICATION AND DATA ANALYSIS
Objective: Introduce the students to statistical learning methods for mathematical model building from experimental data.
Outcomes: A student who has met the objectives of the course should have acquired a fundamental knowledge of modern statistical learning methods and of the numerical algorithms for model estimation and model-based prediction and decision making. Should also acquire a basic understanding of deterministic and stochastic methods for time series and dynamical model identification.
Exams: Written with optional computer project. Two Partial tests during the academic year plus four regular exam sessions.
SYSTEM IDENTIFICATION AND DATA ANALYSIS
Objective: Introduce the students to statistical learning methods for mathematical model building from experimental data.
Outcomes: A student who has met the objectives of the course should have acquired a fundamental knowledge of modern statistical learning methods and of the numerical algorithms for model estimation and model-based prediction and decision making. Should also acquire a basic understanding of deterministic and stochastic methods for time series and dynamical model identification.
Exams: Written with optional computer project. Two Partial tests during the academic year plus four regular exam sessions.
- Docente: Giorgio Picci