OVERVIEW

The course presents the main modelling techniques for complex dynamical processes related to systems engineering and financial engineering. Moreover, the course addresses the identification methods necessary to evaluate the parameters present in the presented models.

AIMS AND CONTENT

LEARNING OUTCOMES

Knowing the main modelling classes for dynamic processes with attention to those adopted in management engineering; defining a class of candidate models for a specific dynamic process; knowing the features of a parameter identification problem; designing the solution of an identification problem; analyzing the convergence properties of the adopted solution algorithm.

AIMS AND LEARNING OUTCOMES

The learning outcomes of the course refer to the capacity of:

• understand the dynamic features of a process;
• define a model suitable for representing the process and fulfil the objectives of the required analysis;
• knowing the features of an identification problem;
• knowing the most important classes of identification models;
• designing the solution to an identification problem;
• knowing the features of a parameter estimation problem;
• designing the solution to a parameter estimation problem.

PREREQUISITES

The course prerequisites refer to basic elements of dynamic systems theory, statistics and optimization.

TEACHING METHODS

The course offers classroom lessons covering theoretical concepts alongside the solution of numerical problems and the use of relevant software frameworks.

Students with valid certifications for Specific Learning Disorders (SLD), disabilities, or other educational needs are invited to contact the teacher and the disability referent of the Polytechnic School, Prof. Federico Scarpa (federico.scarpa@unige.it), at the beginning of the course to discuss potential teaching methods that, while respecting the course objectives, take individual learning styles into account.

Student workers can contact the teacher at the beginning of the course to receive information about the teaching materials.

SYLLABUS/CONTENT

Definition of the main features of dynamic systems and to the main modelling classes. Introduction to the most important dynamic models adopted in management engineering and financial engineering.

Identification techniques: definition of the parameter identification problem, model families (ARX, ARMAX, OE,  ARXAR, BJ),  MPE identification: convergence theorems, identification for ARX models (least squares identification), for ARMAX models and for ARXAR models, batch and iterative algorithms.

Parametric and Bayesian estimation techniques.

RECOMMENDED READING/BIBLIOGRAPHY

All teaching materials will be available on Aulaweb. Generally, notes taken during lessons and the slides provided on Aulaweb are sufficient to meet the learning objectives.

A potential book for comprehensive analysis is the following:

L. Ljung, "System Identification: Theory for the user", Prentice Hall (2nd Edition), 1999.

TEACHERS AND EXAM BOARD

LESSONS

LESSONS START

https://corsi.unige.it/en/corsi/11956/studenti-orario

Class schedule

The timetable for this course is available here: Portale EasyAcademy

EXAMS

EXAM DESCRIPTION

The exam is an oral presentation.

ASSESSMENT METHODS

During the exam the student has to present the main arguments of the course, to solve numerical exercises and to explain the theoretical notions necessary for their solution

FURTHER INFORMATION

Students with certified SLD, disabilities, or other special educational needs are advised to contact the teacher at the beginning of the course to agree on assessment methods, considering individual learning needs while respecting the teaching objectives.

Student workers are advised to contact the teacher to agree on assessment methods.