Continuous time filter design automation
Leuven | Just now
Project Introduction
In any Analog Front End (AFE), the filter is one of the key components for optimizing system performance. It not only improves the signal-to-noise ratio (SNR) by removing out-of-band noise but can also mitigate perturbations, such as adjacent carriers, in certain cases.
Practically, filter design specifications include parameters such as out-of-band rejection, phase distortion/in-band group delay, in-band distortion, and more. Based on these requirements, designers must select the optimal transfer function and the most suitable implementation approach (e.g., gm-C, OpAmp-based).
In this Master Thesis/Internship, the student will develop a Python code to generate semi-automated design of continuous filters, starting from high-level specifications.
Main Tasks
Developing a Python code:
- Transfer function selection
- LC circuit equivalent
- gmC circuit equivalent
- second order active filter equivalent
- AC and noise simulation (Modified Nodal Analysis)
- Filter optimization (noise, power, area)
Type of project: Thesis
Duration: 6 months
Required degree: Master of Engineering Technology
Required background: Electrotechnics/Electrical Engineering
Supervising scientist(s): For further information or for application, please contact: Laurent Berti (Laurent.Berti@imec.be)