OVERVIEW

This course 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: analog (both passive and active), digital (also adaptive), and based on switched capacitors. The main working tools will be PSPICE, MATLAB and laboratory equipment.

AIMS AND CONTENT

LEARNING OUTCOMES

To be able to design analog and digital filters, starting from assigned technical specifications, to simulate them and implement most of them.

AIMS AND LEARNING OUTCOMES

Aims

This course has the following main targets:

•  provide basic knowledge about the synthesis of circuits and sistems for signal filtering

•  provide knowledge about lab instruments (oscilloscope, signal generator, breadboard, connection cables, probes)

•  provide tools for the design of analog and digital filters

•  provide criteria for the choice of a the tool most suitable to solve a given filtering problem

•  consolidate through application to physical systems (the filters) background knowledge of signal processing, circuit theory, system theory, electronics, automation

•  illustrate through examples how to apply the design techniques introduced during the lessons

•  stimulate the communication skills of the students, encouraging small-group activities and giving the possibility of taking part of the exam by taking lab classes

•   develop a capacity for independent study and critical evaluation of topics covered during the course

Expected learning outcomes

At the end of this course, the student should be able to:

•  understand and correctly use the technical language for the description of filters

•  understand the basic principles of filter design techniques

•  apply these principles to design filters, both analog and digital, starting from a set of assigned specifications, as shown during the classroom lectures

•  simulate and (for the kinds of filters physically realized and tested during the lab classes) implement filters

•  for a given problem, decide which filters can (or must) be used to solve it

•  apply to filters background knowledge of signal theory, circuit theory, system theory, electronics, automation

•  work in group and clearly communicate his/her thoughts (mainly for the students that choose the exam mode based on "flipped classroom" and “team-based learning”)

•  independently study and critically evaluate topics covered during the course

The capacity of solving non-trivial problems is one of the main elements of the scientific cultural baggage of an engineer.

Acquisition of soft skills

This course encourages - in particular through the exam mode 1) - the acquisition of soft skills such as literacy competence, personal competence, social competence, ability to learn how to learn.

PREREQUISITES

Basic concepts of circuit theory, system theory, electronics, signal processing, automatic control.

TEACHING METHODS

The topics of the course are presented and illustrated through examples during the frontal lectures (about 30 hours) and applied during the lab activities (about 30 hours). Attending the classes (and in particular the lab activities) is highly touted.

The frontal lectures consist of:

•  traditional teaching based on teacher-led demonstrations and presentation of examples at the blackboard

•  PowerPoint presentations

•  videos

The lab activities are based on the use of:

•  simulation tools (PSPICE, Matlab)

•  lab tools (breadboard, multimeter, oscilloscope, function generator, power supply)

The lab activities are usually taken in "flipped classroom" mode, with students that will prepare them in small (2-4) groups (team-based learning) and lead them or part of them individually, under the guidance of the teacher and a tutor. This will support the acquisition of basic level personal and social skills and basic functional literacy skills. The teacher's habit of offering food for thought and points for discussion during lessons will favor the acquisition of metacognition skills (basic level personal skills, basic level learning-how-to-learn skills).

Students with valid certifications for Specific Learning Disorders (SLDs), disabilities or other educational needs are invited to contact the teacher and the School's contact person for disability at the beginning of teaching to agree on possible teaching arrangements that, while respecting the teaching objectives, take into account individual learning patterns. Contacts of the School's disability contact person can be found at the following link Comitato di Ateneo per l’inclusione delle studentesse e degli studenti con disabilità o con DSA | UniGe | Università di Genova

SYLLABUS/CONTENT

Synthesis of RLC and LC immittances

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

Butterworth filters (design techniques, HW lab activity)

Chebyschev filters (design techniques, HW lab activity)

Elliptic filters (notes on design techniques, HW lab activity)

Bessel filters (notes)

Digital filters (FIR and IIR filters design techniques, Matlab activity)

Adaptive filters (design techniques, Matlab activity)

RC active filters (design techniques, HW lab activity)

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.

The above bibliography should be suitable also for students with valid certifications for Specific Learning Disorders (SLDs), disabilities or other educational needs. Otherwise, they can contact the teacher.

TEACHERS AND EXAM BOARD

LESSONS

LESSONS START

See

https://easyacademy.unige.it/portalestudenti/index.php?view=easycourse&_lang=it&include=corso

Class schedule

ANALOG AND DIGITAL FILTERS LAB

EXAMS

EXAM DESCRIPTION

Two possible modalities:

-) Teaching lessons ("flipped classroom") + oral (discussion concerned with the topics treated during the lessons and to the design techniques applied during lab activities).

-) 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.

In any case, the grading will depend on the degree of acquisition of the expected learning outcomes.

Students with learning disorders ("disturbi specifici di apprendimento", DSA) will be allowed to use specific modalities and supports that will be determined on a case-by-case basis.

ASSESSMENT METHODS

The learning results are assessed individually either

1) through the lab activities (max. 20 marks) and an oral exam (max. 10 marks)

or

2) through an oral exam (max. 30 marks)

According to the specific modality, the assessment will be based on:

-) communication skills (both)

-) knowledge and comprehension of the subject topics (both)

-) knowledge and skillnesses in using the SW packages (PSPICE, Matlab) (for mode 1)

-) ability to compare the features of different kinds of filters, evaluating pros and cons of each choice (both)

-) autonomy of judgment in making filter design choices (both)

-) capacity of working in group (for mode 1)

-) capacity of reproducing the demonstrations shown by the teacher during the frontal lectures (for mode 2)

FURTHER INFORMATION

Students who have valid certification of physical or learning disabilities on file with the University and who wish to discuss possible accommodations or other circumstances regarding lectures, coursework and exams, should refer to the University regulation for the inclusion and right to study of students with disabilities or specific learning disorders (DSA).