Studying at the University of Verona
Here you can find information on the organisational aspects of the Programme, lecture timetables, learning activities and useful contact details for your time at the University, from enrolment to graduation.
Study Plan
This information is intended exclusively for students already enrolled in this course.If you are a new student interested in enrolling, you can find information about the course of study on the course page:
Laurea in Bioinformatica - Enrollment from 2025/2026The Study Plan includes all modules, teaching and learning activities that each student will need to undertake during their time at the University.
Please select your Study Plan based on your enrollment year.
1° Year
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2° Year activated in the A.Y. 2019/2020
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1 module to be chosen among the following3° Year activated in the A.Y. 2020/2021
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1 module to be chosen among the following| Modules | Credits | TAF | SSD |
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1 module to be chosen among the following| Modules | Credits | TAF | SSD |
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1 module to be chosen among the followingLegend | Type of training activity (TTA)
TAF (Type of Educational Activity) All courses and activities are classified into different types of educational activities, indicated by a letter.
Matlab-Simulink programming (2020/2021)
Teaching code
4S007126
Teacher
Coordinator
Credits
2
Also offered in courses:
- Matlab-Simulink programming of the course Bachelor's degree in Computer Science
- Matlab-Simulink programming of the course Master's degree in Computer Science and Engineering
- Matlab-Simulink programming of the course Master's degree in Medical Bioinformatics
- Matlab-Simulink programming of the course Master's degree in Computer Engineering for Robotics and Smart Industry
Language
Italian
Scientific Disciplinary Sector (SSD)
NN - -
Period
I semestre dal Oct 1, 2020 al Jan 29, 2021.
Learning outcomes
Acquisition of adequate skills for programming in the MATLAB environment.
Use of specific tools for solving some problems of the 'Systems' course: block diagrams, transfer functions, Bode plots, Laplace transform.
Create and edit models in Simulink and simulate dynamic systems. Configure solver options to improve simulation accuracy and speed.
Various functions, toolboxes and 'Apps' environment. Convolutional Neural Networks in Matlab.
Program
1. Vectors and Matrices in MATLAB
2. MATLAB Programming
3. Loop Statements and Vectorizing Code
4. More Advanced MATLAB Programs
5. String Manipulation
6. Data Structures: Cell Arrays and Structures
7. Introduction to image processing
8. Dynamic systems with Simulink
9. 'Apps' environment. Convolutional Neural Networks for image classification.
Schedule:
14 April 2021 1:40-4:10 PM
20 April 2021 1:40-4:10 PM
27 April 2021 1:40-4:10 PM
5 May 2021 1:40-4:10 PM
12 May 2021 1:40-4:10 PM
19 May 2021 1:40-4:10 PM
26 May 2021 1:40-4:10 PM
2 June 2021 1:40-4:10 PM
| Author | Title | Publishing house | Year | ISBN | Notes |
|---|---|---|---|---|---|
| Dalle lezioni | Appunti dalle lezioni | 2021 | |||
| Stormy Attaway | Matlab: A Practical Introduction to Programming and Problem Solving (Edizione 3) | Elsevier | 2013 | 978-0-12-405876-7 |
Examination Methods
The final exam consists of a written quiz.
The students may ask for a small project that substitutes the written exam.
