The specialisation is comprised of 20 ECTS core courses. You must select 20 ECTS from the specialisation elective courses. You may take some or all the remaining of these courses as your normal elective courses if you desire.

The specialisation is comprised of 20 ECTS core courses. You must select 20 ECTS from the specialisation elective courses. You may take some or all the remaining of these courses as your normal elective courses if you desire.

Core Courses

Integrated Circuits (10 ECTS)

This course gives a thorough understanding of integrated circuit design with emphasis on CMOS technology for the design of digital integrated circuits and basic analog circuit blocks. You will after the course have a firm grounding in the fundamentals of analysis and design of integrated circuits with emphasis on CMOS technology. The course aims to focus on practical matters of IC design, and on intuitive understanding of circuit behavior as opposed to heavily analytical approaches.

Very Large-Scale Integration (VLSI) Design (5 ECTS)

The course content: Integrated electronic devices; digital integrated circuits; very large scale integration systems; low-power architectures and their building blocks; low-power circuit design challenges; system and circuit specifications; design constraints and technology limitations; advanced system architectures, circuit topologies and state-of-the-art design techniques for the main building blocks; latest advances in the state of the art, CMOS scaling challenges and beyond CMOS technologies; VHDL programming; ASIC design.

MEMS and Sensors (5 ECTS)

The course will primarily describe and discuss the most widely used and well-known processes within micro- and nanofabrication, such as:

• Lithography (UV photolithography, e-beam- and nanoimprint-lithography)
• Etching (wet chemical, reactive ion etching (RIE), laser)
• Metallization (sputtering, e-beam evaporation, plating)
• Lift-off
• Thermal diffusion (doping)
• Ion implantation
• Oxidation
• Thin film deposition (LP-/PE-CVD, PVD, ALD)
• Laser doping
• Furthermore, this course will provide examples of how these processes can be combined in suitable process flows to fabricate certain MEMS and sensor devices.
• The course will go through the most important materials and their physical, chemical, mechanical, electrical and optical properties. Focus will be on semiconductors like Si (crystalline, poly-Si and amorphous) and the III-V group, plus oxides/nitrides, metals and polymers.
• In addition, this course will have a focus on the most important underlying semiconductor physics, such as pn-junctions, atomic movements in solids and light-matter interaction.
• Finally, you will each be asked to select a specific device, for which you should design a process flow including simulating process parameters and properties. You will present your findings for the class.

Specialisation Elective Courses

Electronic Hardware System Design (5 ECTS)

The course teaches design principles of modern and complex electronic hardware systems at board and platform level with focus on high-speed digital/mixed-signal design. Several design issues are important to address when designing (high-speed) digital systems and/or mixed-signal systems. Design challenges relate to power supply distribution and noise budget, interconnections and their impact to performance and signal integrity and coupling, packaging design, etc.

In the course, we will explore key/state-of-the-arts interconnect technologies from chip level to system level. We will study topics like:

• Interconnect and packing modeling,
• Digital signal integrity in high-speed electronics,
• Power supply noise and grounding,
• Power distribution system and decoupling allocation
• Digital timing analysis at the system level
   

The course theory and design methodologies will throughout the course be exemplified by labs and exercises

RF System Design (5 ECTS)

The course objective is to provide you with an insight in modern RF/microwave analysis and design techniques. Both wireless communication and sensor applications are covered in the course. You are presented to system-level RF/microwave analysis and design, RF/microwave circuit interface challenges and state-of-the-art simulation techniques. Furthermore, a comprehensive introduction to integrated PCB and microwave antenna analysis and design is provided as well as hands-on experience with RF/microwave measurement techniques including anechoic chamber antenna measurements.

ETANT-01 Antenner (5 ECTS)

Key antenna concepts such as radiation pattern, directivity, gain, polarization and antenna noise temperature. Analysis and design of frequently occurring antenna types such as wire, printed, horn, patch, reflector and slot antennas. Analysis and design of antenna groups, including phased arrays. Practical construction of wire and printed antennas and measurement of key parameters on these antennas in a dedicated measurement facility. Case-based introduction to system analysis based on existing radar and wireless communication systems.

ETMBED-01 Design of Microwave Electronics (5 ECTS)

S-parameters. Measurement techniques: signal generators, spectrum and network analysers. Microstrip design. Microwave amplifiers: Low noise amplifiers and power amplifiers. Microwave oscillators (including dielectric resonance oscillators). Microwave PLL: Integer-N and Fractional-N. Simulation tool: Microwave Office

Deep Learning (10 ECTS)

The course offers a general introduction to neural networks and Deep Learning models. The course starts with the study of simple neural networks and a description of fundamental concepts, such as activation functions and optimization through backpropagation. After that we gradually introduce more advanced concepts and processing blocks/steps to our networks, while discussing their properties and possible usage. Emphasis will be on established methods, such as convolutional layers, fully connected layers, pooling layers and recurrent layers, such as the Long- Short-Term Memory layer. In parallel to the description of the concepts and methodologies in the lectures, programming exercise sessions will be held in which these concepts and methodologies are explored on a weekly basis. 

At the end of the course, you will be able to design and implement Deep Learning to study a specific data set of their own choice.  

Advanced Signal Processing (10 ECTS)

The objective of the course is to give you insight into advanced signal processing methods applicable for processing noisy real-world, discrete-time stationary and nonstationary signals. You will gain experience with methods for analysis, filtering, reconstruction, and prediction of stochastic signals based on advanced signal processing methods. The course focus on 1-dimensional data sets, e.g., timeseries with examples drawn throughout acoustics, biomedical engineering, earth sciences, and electronics.