Embedded Software

Course guarantor:

Lecturer:

Tutor:

Supervisor:

Department of Digital Design

Synopsis:

The course introduces students to the principles and distinctive features of software development for embedded systems. It leads students from the basics of programming in C and code optimization through key topics such as reliable software design, embedded operating systems, and signal processing, culminating in advanced methods that integrate embedded software development with artificial intelligence.

Requirements:

Syllabus of lectures:

1. Software in embedded systems.

2. Programming languages and high level synthesis

3. Code optimization with respect to power consumption, resources and performance.

4. Model-based design and HW/SW co-design.

5. Reliable software development, debugging, and testing.

6. Operating systems for embedded systems.

7. Signal processing.

8. Digital filters and their implementation.

9. Software for control applications.

10. Programming of industrial robots.

11. Artificial intelligence in embedded systems.

12. AI model optimization for systems with limited resources and computational power.

13. Development of autonomous systems.

Syllabus of tutorials:

bude doplněno

Study Objective:

The course introduces students to the principles and distinctive features of software development for embedded systems. It leads students from the basics of programming in C and code optimization through key topics such as reliable software design, embedded operating systems, and signal processing, culminating in advanced methods that integrate embedded software development with artificial intelligence.

Study materials:

1. Hobbs, C.: Embedded Software Development for Safety-Critical Systems (2st Edition). Auerbach Publications, 2019. ISBN 978-0367338855.

2. Fan, X.: Real-Time Embedded Systems: Design Principles and Engineering Practices. Newnes, 2015. ISBN 978-0128015070.

3. Lynch, K. M. - Park, F. C.: Modern Robotics: Mechanics, Planning, and Control. Cambridge University Press, 2017. ISBN Cambridge University Press.

4. P. P. Vaidyanathan: Continuous Signals and Systems with MATLAB. Cambridge: Cambridge University Press, 2024. ISBN 978-1009412292.

5. Dinwiddie, K.: Industrial Robotics.Cengage Learning (1st Edition). Delmar Cengage Learning, 2018. ISBN 978-1133610991.

6. Moons, B. - Bankman, D. - Verhelst, M.: Embedded Deep Learning: Algorithms, Architectures and Circuits for Always-on Neural Network Processing. Springer, 2018. ISBN 978-3319992228.

Note:

Further information:

https://courses.fit.cvut.cz

No time-table has been prepared for this course

The course is a part of the following study plans: