Admission requirements
Experimental physics parts 1 and 2. Prior knowledge of Optics, Classical Mechanics, Analysis 3 NA and Physics Experiments 1
Description
This course builds on the knowledge about signal processing that you gained from Physics Experiments 1 and extends it towards more complex systems that involve positive and negative feedback and various sources of noise. The ultimate goal is to prepare you to independently set up a complex experiment. This will be tested during Physics Experiments 3.
During the course we will analyze various sources of noise and interference and show you how to handle them. Furthermore, we will discuss (positive and negative) feedback, Fourier and Laplace transforms and simple control theory.
To gain both the necessary theoretical background and direct practical experience this course consists of a combination of lectures, exercise classes, and practical work. Python is used in both the exercise classes and the practical work. Because of this structure, you will not only get to know a powerful theory that is applicable to many physical phenomena, but also be able to use that theory in practice.
This course treats the following subjects in a physically relevant context:
2D Fourier transform and Fourier optics
Step and impulse response
Laplace transform
Feedback
Noise
OpAmp
Course objectives
After successful completion of this course you will be able to do the following in both a theoretical as well as experimental context:
Analyze, build and measure simple electronic circuits containing resistors, capacitors, inductors and OpAmps.
Analyze linear time-invariant systems in the time domain and in the frequency domain:
- Apply mathematical tools to signals: convolution and various Fourier transforms.
- Perform simple image processing using 2D Fourier transforms.
- Derive, measure and plot impulse response, step response and transfer functions of electronic and mechanical systems.
- Recognize, identify and derive the origin of various artifacts in analog to digital conversion and sampling, such as aliasing, spectral leakage and vertical resolution.
Analyze stochastic (random) signals such as noise:
- Using statistical analysis, autocorrelation, the Wiener-Khinchin theorem and noise spectral densities.
- Describe the cause, spectrum, and consequences of various sources of noise and interference and propose solutions to improve signal-to-noise ratio.
Determine the stability of negative and positive feedback systems:
- Performing the Laplace transform and the BIBO stability criterion.
- Using the Nyquist stability criterion.
Schedule
The timetables are available through My Timetable (see the button in the upper right corner).
Teaching method
Lab work, lectures (in Dutch), exercises/exam are in English
See Brightspace
Assesment method
Lab work, assignments/exercises and exam (all in English)
Resit, review & feedback
Examinations are held twice during the academic year for each component offered in that academic year. Midterm tests cannot be retaken. The Board of Examiners determines the manner of resit for practical assignments.
For review and feedback, see Brightspace.
Reading list
There will be a reader available (English).
Registration
Enrolment through MyStudyMap (button in upper right corner) is mandatory. General information about course and exam enrolment is available on the website.
Contact
For substantive questions, contact the lecturer(s) (listed in the right information bar).
Lecturer for the theoretical part: Dr.ir. B.J. Hensen
Lecturer for the practical part: Dr.ir. Paul Logman and F. Schenkel
Remarks
Software
Starting from the 2024/2025 academic year, the Faculty of Science will use the software distribution platform Academic Software. Through this platform, you can access the software needed for specific courses in your studies. For some software, your laptop must meet certain system requirements, which will be specified with the software. It is important to install the software before the start of the course. More information about the laptop requirements can be found on the student website.