OVERVIEW

This subject aims to provide basic elements for the design and synthesis of analog and digital filters. One half of the lectures is given in laboratory, where the students are driven to design, simulate, implement and test different kinds of filters, by using tools such as PSPICE, MATLAB and laboratory equipment.

AIMS AND CONTENT

LEARNING OUTCOMES

The goal of the course is to provide the basic notions for the design of analog (both passive and active) and digital filters tailored for processing sensor measurements in robotic applications. The topics are proposed to students through both theoretical lessons and practical activities such as the simulation and the hardware realization of filters.

AIMS AND LEARNING OUTCOMES

It is expected that at the end of this subject the student will be able to design analog and digital filters, starting from assigned technical specifications, and to simulate them. Moreover, he/she should be able to implement and test the kinds of filters physically realized and tested during the lectures. To this end, he/she has to learn the main peculiar features of each class of filters and the corresponding design techniques described during the classroom lectures. Given a specific filter design problem, the student has firstly to decide what class of filters can be (or has to be) used to solve it. Then he/she can start designing the filter, by using not only the techniques specific for filters, but also general concepts coming from other areas, such as signal processing and automatic controls, as illustrated during the lectures. This capacity of solving non-trivial problems is one of the main elements of the scientific cultural baggage of an engineer.

PREREQUISITES

Basic concepts of circuit theory, electronics, signal processing, automatic controls.

TEACHING METHODS

About 30 classroom hours and 30 lab hours.

SYLLABUS/CONTENT

Introduction to the course.

Signal-processing chain in robotics applications.
- The boundary between analog and digital blocks: The Nyquist–Shannon sampling theorem.
- Anti aliasing filters.

General concepts about filter synthesis (frequency transforms, ideal and physical filters, adaptation)

Design of analog filters:
- Design of doubly-terminated passive filters: Butterworth, Chebyschev, Elliptic and Bessel filters (design techniques, HW lab activity).
- Design of RC active filters (design techniques, HW lab activity)

Design of  Digital filters:
- FIR filters (design techniques, Matlab activity
- IIR filters (design techniques, Matlab activity
- Adaptive filters (design techniques, Matlab activity)

Design of integrated filters: Switched-capacitor filters (principles, HW lab activity)

RECOMMENDED READING/BIBLIOGRAPHY

- Notes provided by the lecturer (main reference)

- C. Bowik, "RF circuits design," Newnes, 1997.

- J.G. Proakis, D.G. Manolakis, "Digital signal processing: principles, algorithms, and applications," Prentice Hall, 1996.

- M.E. Van Valkenburg, "Analog Filter Design," Oxford University Press, 1995.

- A. Liberatore, S. Manetti, "La progettazione dei filtri elettronici," Edizione Medicea, 1985.

- L.B. Jackson, "Digital filters and signal processing," Kluwer Academic Publishers, 1996.

TEACHERS AND EXAM BOARD

Exam Board

MATTEO LODI (President)

MARCO STORACE

STEFANO ROVETTA (President Substitute)

LESSONS

LESSONS START

Regular (see the calendar at the website https://www.politecnica.unige.it/index.php/didattica-e-studenti/orario)

Class schedule

The timetable for this course is available here: Portale EasyAcademy

EXAMS

EXAM DESCRIPTION

Oral: two discussions starting from two questions (one chosen by the student and one asked by the examiner) concerned with the topics treated during the lessons and to the design techniques applied during lab activities.

ASSESSMENT METHODS

The learning results are assessed through the lab activities and the oral exam.

Exam schedule