Search result: Catalogue data in Autumn Semester 2022
Electrical Engineering and Information Technology Master ![]() | ||||||||||||||||||
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![]() ![]() A total of 42 CP must be achieved during the Master Programme. The individual study plan is subject to the tutor's approval. | ||||||||||||||||||
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![]() ![]() ![]() ![]() These core subjects are particularly recommended for the field of "Electronics and Photonics". | ||||||||||||||||||
Number | Title | Type | ECTS | Hours | Lecturers | |||||||||||||
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227-0146-00L | Analog-to-Digital Converters ![]() | W | 6 credits | 2V + 2U | T. Burger | |||||||||||||
Abstract | This course provides a thorough treatment of integrated data conversion systems from system level specifications and trade-offs, over architecture choice down to circuit implementation. | |||||||||||||||||
Learning objective | Data conversion systems are substantial sub-parts of many electronic systems, e.g. the audio conversion system of a home-cinema systems or the base-band front-end of a wireless modem. Data conversion systems usually determine the performance of the overall system in terms of dynamic range and linearity. The student will learn to understand the basic principles behind data conversion and be introduced to the different methods and circuit architectures to implement such a conversion. The conversion methods such as successive approximation or algorithmic conversion are explained with their principle of operation accompanied with the appropriate mathematical calculations, including the effects of non-idealties in some cases. After successful completion of the course the student should understand the concept of an ideal ADC, know all major converter architectures, their principle of operation and what governs their performance. | |||||||||||||||||
Content | - Introduction: information representation and communication; abstraction, categorization and symbolic representation; basic conversion algorithms; data converter application; tradeoffs among key parameters; ADC taxonomy. - Dual-slope & successive approximation register (SAR) converters: dual slope principle & converter; SAR ADC operating principle; SAR implementation with a capacitive array; range extension with segmented array. - Algorithmic & pipelined A/D converters: algorithmic conversion principle; sample & hold stage; pipe-lined converter; multiplying DAC; flash sub-ADC and n-bit MDAC; redundancy for correction of non-idealties, error correction. - Performance metrics and non-linearity: ideal ADC; offset, gain error, differential and integral non-linearities; capacitor mismatch; impact of capacitor mismatch on SAR ADC's performance. - Flash, folding an interpolating analog-to-digital converters: flash ADC principle, thermometer to binary coding, sparkle correction; limitations of flash converters; the folding principle, residue extraction; folding amplifiers; cascaded folding; interpolation for folding converters; cascaded folding and interpolation. - Noise in analog-to-digital converters: types of noise; noise calculation in electronic circuit, kT/C-noise, sampled noise; noise analysis in switched-capacitor circuits; aperture time uncertainty and sampling jitter. - Delta-sigma A/D-converters: linearity and resolution; from delta-modulation to delta-sigma modulation; first-oder delta-sigma modulation, circuit level implementation; clock-jitter & SNR in delta-sigma modulators; second-order delta-sigma modulation, higher-order modulation, design procedure for a single-loop modulator. - Digital-to-analog converters: introduction; current scaling D/A converter, current steering DAC, calibration for improved performance. | |||||||||||||||||
Lecture notes | Slides are available online under https://iis-students.ee.ethz.ch/lectures/analog-to-digital-converters/ | |||||||||||||||||
Literature | - B. Razavi, Principles of Data Conversion System Design, IEEE Press, 1994 - M. Gustavsson et. al., CMOS Data Converters for Communications, Springer, 2010 - R.J. van de Plassche, CMOS Integrated Analog-to-Digital and Digital-to-Analog Converters, Springer, 2010 | |||||||||||||||||
Prerequisites / Notice | It is highly recommended to attend the course "Analog Integrated Circuits" of Prof. T. Jang as a preparation for this course. | |||||||||||||||||
227-0147-10L | VLSI 3: Full-Custom Digital Circuit Design ![]() | W | 6 credits | 2V + 3U | C. Studer, O. Castañeda Fernández | |||||||||||||
Abstract | This third course in our VLSI series is concerned with full-custom digital integrated circuits. The goals include learning the design of digital circuits on the schematic, layout, gate, and register-transfer levels. The use of state-of-the-art CAD software (Cadence Virtuoso) in order to simulate, optimize, and characterize digital circuits is another important topic of this course. | |||||||||||||||||
Learning objective | At the end of this course, you will • understand the design of the main building blocks of state-of-the-art digital integrated circuits • be able to design and optimize digital integrated circuits on the schematic, layout, and gate levels • be able to use standard industry software (Cadence Virtuoso) for drawing, simulating, and characterizing digital circuits • understand the performance trade-offs between delay, area, and power consumption | |||||||||||||||||
Content | The third VLSI course begins with the basics of metal-oxide-semiconductor (MOS) field-effect transistors (FETs) and moves up the stack towards logic gates and increasingly complex digital circuit structures. The topics of this course include: • Nanometer MOSFETs • Static and dynamic behavior of complementary MOS (CMOS) inverters • CMOS gate design, sizing, and timing • Full-custom standard-cell design • Wire models and parasitics • Latch and flip-flop circuits • Gate-level timing analysis and optimization • Static and dynamic power consumption; low-power techniques • Alternative logic styles (dynamic logic, pass-transistor logic, etc.) • Arithmetic and logic circuits • Fixed-point and floating-point arithmetic • Synchronous and asynchronous design principles • Memory circuits (ROM, SRAM, and DRAM) • In- and near-memory processing architectures • Full-custom accelerator circuits for machine learning The exercises are concerned with schematic entry, layout, and simulation of digital integrated circuits using a disciplined standard-cell-based approach with Cadence Virtuoso. | |||||||||||||||||
Literature | N. H. E. Weste and D. M Harris, CMOS VLSI Design: A Circuits and Systems Perspective (4th Ed.), Addison-Wesley | |||||||||||||||||
Prerequisites / Notice | VLSI 3 can be taken in parallel with “VLSI 1: HDL-based design for FPGAs” and is designed to complement the topics of this course. Basic analog circuit knowledge is required. | |||||||||||||||||
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227-0301-00L | Optical Communication Fundamentals | W | 6 credits | 2V + 1U + 1P | J. Leuthold | |||||||||||||
Abstract | The path of an analog signal in the transmitter to the digital world in a communication link and back to the analog world at the receiver is discussed. The lecture covers the fundamentals of all important optical and optoelectronic components in a fiber communication system. This includes the transmitter, the fiber channel and the receiver with the electronic digital signal processing elements. | |||||||||||||||||
Learning objective | An in-depth understanding on how information is transmitted from source to destination. Also the mathematical framework to describe the important elements will be passed on. Students attending the lecture will further get engaged in critical discussion on societal, economical and environmental aspects related to the on-going exponential growth in the field of communications. | |||||||||||||||||
Content | * Chapter 1: Introduction: Analog/Digital conversion, The communication channel, Shannon channel capacity, Capacity requirements. * Chapter 2: The Transmitter: Components of a transmitter, Lasers, The spectrum of a signal, Optical modulators, Modulation formats. * Chapter 3: The Optical Fiber Channel: Geometrical optics, The wave equations in a fiber, Fiber modes, Fiber propagation, Fiber losses, Nonlinear effects in a fiber. * Chapter 4: The Receiver: Photodiodes, Receiver noise, Detector schemes (direct detection, coherent detection), Bit-error ratios and error estimations. * Chapter 5: Digital Signal Processing Techniques: Digital signal processing in a coherent receiver, Error detection teqchniques, Error correction coding. * Chapter 6: Pulse Shaping and Multiplexing Techniques: WDM/FDM, TDM, OFDM, Nyquist Multiplexing, OCDMA. * Chapter 7: Optical Amplifiers : Semiconductor Optical Amplifiers, Erbium Doped Fiber Amplifiers, Raman Amplifiers. | |||||||||||||||||
Lecture notes | Lecture notes are handed out. | |||||||||||||||||
Literature | Govind P. Agrawal; "Fiber-Optic Communication Systems"; Wiley, 2010 | |||||||||||||||||
Prerequisites / Notice | Fundamentals of Electromagnetic Fields & Bachelor Lectures on Physics. | |||||||||||||||||
227-0517-10L | Fundamentals of Electric Machines ![]() | W | 6 credits | 4G | D. Bortis, R. Bosshard | |||||||||||||
Abstract | This course introduces to different electric machine concepts and provides a deeper understanding of their detailed operating principles. Different aspects arising in the design of electric machines, like dimensioning of magnetic and electric circuits as well as consideration of mechanical and thermal constraints, are investigated. The exercises are used to consolidate the concepts discussed. | |||||||||||||||||
Learning objective | The objective of this course is to convey knowledge on the operating principles of different types of electric machines. Further objectives are to evaluate machine types for given specifications and to acquire the ability to perform a rough design of an electrical machine while considering the versatile aspects with respect to magnetic, electrical, mechanical and thermal limitations. Exercises are used to consolidate the presented theoretical concepts. | |||||||||||||||||
Content | ‐ Fundamentals in magnetic circuits and electromechanical energy conversion. ‐ Force and torque calculation. ‐ Operating principles, magnetic and electric modelling and design of different electric machine concepts: DC machine, AC machines (permanent magnet synchronous machine, reluctance machine and induction machine). ‐ Complex space vector notation, rotating coordinate system (dq-transformation). ‐ Loss components in electric machines, scaling laws of electromechanical actuators. ‐ Mechanical and thermal modelling. | |||||||||||||||||
Lecture notes | Lecture notes and associated exercises including correct answers | |||||||||||||||||
227-0663-00L | Nano-Optics ![]() | W | 6 credits | 2V + 2U | M. Frimmer | |||||||||||||
Abstract | Nano-Optics is the study of light-matter interaction at the sub-wavelength scale. It is an flourishing field of fundamental and applied research enabled by the rapid advance of nanotechnology. Nano-optics embraces topics such as plasmonics, optical antennas, optical trapping and manipulation, and high/super-resolution imaging and spectroscopy. | |||||||||||||||||
Learning objective | Understanding concepts of light localization and light-matter interactions on the sub-wavelength scale. | |||||||||||||||||
Content | We start with the angular spectrum representation of fields to understand the classical resolution limit. We continue with the theory of strongly focused light, the point spread function, and resolution criteria of conventional microscopy, before turning to super-resolution techniques, based on near- and far-fields. We introduce the local density of states and approaches to control spontaneous emission rates in inhomogeneous environments, including optical antennas. Finally, we touch upon optical forces and their applications in optical tweezers. | |||||||||||||||||
Prerequisites / Notice | - Electromagnetic fields and waves (or equivalent) - Physics I+II | |||||||||||||||||
227-0655-00L | Nonlinear Optics | W | 6 credits | 2V + 2U | J. Leuthold | |||||||||||||
Abstract | Nonlinear Optics deals with the interaction of light with matter. I.e. the response of insulators, metals, semiconductors or metamaterials to light and the mathematical framework (classical and quantum mechanical) to describe the phenomena. It is the goal to understand phenomena such as the refractive index, the electro-optic effect, rectification, harmonic generation, FWM, soliton propagation,... | |||||||||||||||||
Learning objective | The important nonlinear optical phenomena are understood and can be classified. The effects can be described mathematical by means of the susceptibility. Particpants will be able to desing and invent novel photonic, plasmonic or quantum devices. | |||||||||||||||||
Content | Chapter 1: The Wave Equations in Nonlinear Optics Chapter 2: Nonlinear Effects - An Overview Chapter 3: The Nonlinear Optical Susceptibility - Classical and Quantummechanical Derivations Chapter 4: Second Harmonic Generation Chapter 5: The Electro-Optic Effect and the Electro-Optic Modulator Chapter 6: Acousto-Optic Effect Chapter 7: Nonlinear Effects of Third Order Chapter 8: Nonlinear Effects in Media with Gain | |||||||||||||||||
Literature | Lecture notes are distributed. For students enrolled in the course, additional information, lecture notes and exercises can be found on moodle (https://moodle-app2.let.ethz.ch/). | |||||||||||||||||
Prerequisites / Notice | Fundamentals of Electromagnetic Fields (Maxwell Equations) & Bachelor Lectures on Physics | |||||||||||||||||
227-1033-00L | Neuromorphic Engineering I ![]() Registration in this class requires the permission of the instructors. Class size will be limited to available lab spots. Preference is given to students that require this class as part of their major. Information for UZH students: Enrolment to this course unit only possible at ETH. No enrolment to module INI404 at UZH. Please mind the ETH enrolment deadlines for UZH students: https://ethz.ch/en/studies/non-degree-courses/special-students.html | W | 6 credits | 2V + 3U | T. Delbrück, G. Indiveri, S.‑C. Liu | |||||||||||||
Abstract | This course covers analog circuits with emphasis on neuromorphic engineering: MOS transistors in CMOS technology, static circuits, dynamic circuits, systems (silicon neuron, silicon retina, silicon cochlea) with an introduction to multi-chip systems. The lectures are accompanied by weekly laboratory sessions. | |||||||||||||||||
Learning objective | Understanding of the characteristics of neuromorphic circuit elements. | |||||||||||||||||
Content | Neuromorphic circuits are inspired by the organizing principles of biological neural circuits. Their computational primitives are based on physics of semiconductor devices. Neuromorphic architectures often rely on collective computation in parallel networks. Adaptation, learning and memory are implemented locally within the individual computational elements. Transistors are often operated in weak inversion (below threshold), where they exhibit exponential I-V characteristics and low currents. These properties lead to the feasibility of high-density, low-power implementations of functions that are computationally intensive in other paradigms. Application domains of neuromorphic circuits include silicon retinas and cochleas for machine vision and audition, real-time emulations of networks of biological neurons, and the development of autonomous robotic systems. This course covers devices in CMOS technology (MOS transistor below and above threshold, floating-gate MOS transistor, phototransducers), static circuits (differential pair, current mirror, transconductance amplifiers, etc.), dynamic circuits (linear and nonlinear filters, adaptive circuits), systems (silicon neuron, silicon retina and cochlea) and an introduction to multi-chip systems that communicate events analogous to spikes. The lectures are accompanied by weekly laboratory sessions on the characterization of neuromorphic circuits, from elementary devices to systems. | |||||||||||||||||
Literature | S.-C. Liu et al.: Analog VLSI Circuits and Principles; various publications. | |||||||||||||||||
Prerequisites / Notice | Particular: The course is highly recommended for those who intend to take the spring semester course 'Neuromorphic Engineering II', that teaches the conception, simulation, and physical layout of such circuits with chip design tools. Prerequisites: Background in basics of semiconductor physics helpful, but not required. |
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