Search result: Catalogue data in Spring Semester 2015

Computational Science and Engineering Master Information
Electives
NumberTitleTypeECTSHoursLecturers
151-0834-00LForming Technology II - Introduction Virtual Process Modelling Information W4 credits2V + 2UP. Hora
AbstractThe lecture imparts the principles of the nonlinear Finite-Element-Methods (FEM), implicit and explicit FEM-integration procedures for quasistatic applications, modeling of coupled thermo-mechanical problems, modeling of time dependent contact conditions, modeling of the nonlinear material behaviour, modeling of friction, FEM-based prediction of failure by means of cracks and crinkles.
ObjectiveProzess optimization through numerical methods
ContentApplication of virtual simulation methods for planning and optimization of metal-forming processes. Fundamentals of virtual simulation processes, based on Finite-Element-Methods (FEM) and Finite-Difference-Methods (FDM). Introduction to the basics of continuum and plasto mechanics to mathematically describe the plastic material flow of metals. The procedures to acquire process relevant features. The exercises include the application of industrial simulation tools for deep drawing in automotive applications, high pressure inner metal working (space frame) and rod extrusion.
Lecture notesyes
151-0836-00LVirtual Process Control in Forming Manufacturing Systems Information W5 credits2V + 2UP. Hora
AbstractIntroduction to the methods of virtual modeling of manufacturing processes, illustrated with examples from the digital automotive plant and others. The lecture presents an opportunity to learn the application of non-linear finite element analysis and optimization methods and also adresses stochastical methods for the control of the robust processes.
ObjectiveIntegral study of virtual planning technologies in forming manufacturing systems
ContentIntroduction to the methods of digital plant modeling. Examples: digital automitive plant, digital space-frame manufacturing, digital extrusion plant. Methods: virtual modeling of complex forming processes, non-linear FEA, optimization methods, stochastical methods.
Lecture notesyes
151-0840-00LPrinciples of FEM-Based Optimization and Robustness Analysis Information W5 credits2V + 2UB. Berisha, P. Hora, N. Manopulo
AbstractThe course provides fundamentals of stochastic simulation and non-linear optimization methods. Methods of non-linear optimizaion for complex mechanical systems will be introduced und applied on real processes. Typical applications of stochastical methods for the prediction of process stability and robustness analysis will be discussed.
ObjectiveReal systems are, in general, of non-linear nature. Moreover, they are submitted to process parameter variations. In spite of this, most research is performed assuming deterministic boundary conditions, in which all parameters are constant. As a consequence, such research cannot draw conclusions on real system behavior, but only on behavior under singular conditions. Hence, the objective of this course is to give an insight into stochastic simulations and non-linear optimization methods.

Students will learn mathematical methods e.g. gradient based and gradient free methods like genetic algorithm, and optimization tools (Matlab Optimization Toolbox) to solve basic optimization and stochastic problems.

Furthermore, special attention will be paid to the modeling of engineering problems using a commercial finite element program e.g. LS-Dyna to evaluate the mechanical response of a system, and an optimization tool e.g. LS-Opt for the mathematical optimization and robustness analysis.
ContentPrinciples of nonlinear optimization

- Introduction into nonlinear optimization and stochastic process simulation
- Principles of nonlinear optimization
- Introduction into the design optimization and probabilistic tool LS-Opt
- Design of Experiments DoE
- Introduction into nonlinear finite element methods

Optimization of nonlinear systems

- Application: Optimization of simple structures using LS-Opt and LS-Dyna
- Optimization based on meta modeling techniques
- Introduction into structure optimization
- Introduction into geometry parameterization for shape and topology optimization

Robustness and sensitivity of multiparameter systems

- Introduction into stochastics and robustness of processes
- Sensitivity analysis
- Application examples
Lecture notesyes
151-0206-00LEnergy Systems and Power EngineeringW4 credits2V + 2UR. S. Abhari, A. Steinfeld
AbstractIntroductory first course for the specialization in ENERGY. The course provides an overall view of the energy field and pertinent global problems, reviews some of the thermodynamic basics in energy conversion, and presents the state-of-the-art technology for power generation and fuel processing.
ObjectiveIntroductory first course for the specialization in ENERGY. The course provides an overall view of the energy field and pertinent global problems, reviews some of the thermodynamic basics in energy conversion, and presents the state-of-the-art technology for power generation and fuel processing.
ContentWorld primary energy resources and use: fossil fuels, renewable energies, nuclear energy; present situation, trends, and future developments. Sustainable energy system and environmental impact of energy conversion and use: energy, economy and society. Electric power and the electricity economy worldwide and in Switzerland; production, consumption, alternatives. The electric power distribution system. Renewable energy and power: available techniques and their potential. Cost of electricity. Conventional power plants and their cycles; state-of-the -art and advanced cycles. Combined cycles and cogeneration; environmental benefits. Solar thermal power generation and solar photovoltaics. Hydrogen as energy carrier. Fuel cells: characteristics, fuel reforming and combined cycles. Nuclear power plant technology.
Lecture notesVorlesungsunterlagen werden verteilt
151-0306-00LVisualization, Simulation and Interaction - Virtual Reality I Information W4 credits4GA. Kunz
AbstractTechnology of Virtual Reality. Human factors, Creation of virtual worlds, Lighting models, Display- and acoustic- systems, Tracking, Haptic/tactile interaction, Motion platforms, Virtual prototypes, Data exchange, VR Complete systems, Augmented reality, Collaboration systems; VR and Design; Implementation of the VR in the industry; Human Computer Interfaces (HCI).
ObjectiveThe product development process in the future will be characterized by the Digital Product which is the center point for concurrent engineering with teams spreas worldwide. Visualization and simulation of complex products including their physical behaviour at an early stage of development will be relevant in future. The lecture will give an overview to techniques for virtual reality, to their ability to visualize and to simulate objects. It will be shown how virtual reality is already used in the product development process.
ContentIntroduction to the world of virtual reality; development of new VR-techniques; introduction to 3D-computergraphics; modelling; physical based simulation; human factors; human interaction; equipment for virtual reality; display technologies; tracking systems; data gloves; interaction in virtual environment; navigation; collision detection; haptic and tactile interaction; rendering; VR-systems; VR-applications in industry, virtual mockup; data exchange, augmented reality.
Lecture notesA complete version of the handout is also available in English.
Prerequisites / NoticeVoraussetzungen:
keine
Vorlesung geeignet für D-MAVT, D-ITET, D-MTEC und D-INF

Testat/ Kredit-Bedingungen/ Prüfung:
– Teilnahme an Vorlesung und Kolloquien
– Erfolgreiche Durchführung von Übungen in Teams
– Mündliche Einzelprüfung 30 Minuten
151-0314-00LInformation Technologies in the Digital Product Information W4 credits3GE. Zwicker, R. Montau
AbstractObjective, Methods, Concepts of the Digital Product and Product-Life-Cycle-Management (PLM)
Digital Product Fundamental: Productstructuring, Optimisation of Development- and Engineering Processes, Distribution and Use of Product Data in Sales, Production & Assembly, Service
PLM Fundamentals: Objects, Structures, Processes, Integrations
Application and Best Practices
ObjectiveThe students learn the basics and concepts of the product life cycle management (PLM), the usage of databanks, the integration of CAx-Systems, the configuration of computer networks and their protocols, moderne computer based communication (CSCW) or the variants and configuration management in regard to the creation, administration and usage of digital products.
ContentMöglichkeiten und Potentiale der Nutzung moderner IT-Tools, insbesondere moderner CAx- und PLM- Technologien. Der zielgerichtete Einsatz von CAx- und PLM-Technologien im Zusammenhang Produkt-Plattform - Unternehmensprozesse - IT-Tools. Einführung in die Konzepte des Produkt-Lifecycle-Managements (PLM): Informationsmodellierung, Verwaltung, Revisionierung, Kontrolle und Verteilung von Produktdaten bzw. Produkt-Plattformen. Detaillierter Aufbau und Funktionsweise von PLM-Systemen. Integration neuer IT-Technologien in bestehende und neu zu strukturierende Unternehmensprozesse. Möglichkeiten der Publikation und der automatischen Konfiguration von Produktvarianten auf dem Internet. Einsatz modernster Informations- und Kommunikationstechnologien (CSCW) beim Entwickeln von Produkten durch global verteilte Entwicklungszentren. Schnittstellen der rechnerintegrierten und unternehmensübergreifenden Produktentwicklung. Auswahl und Projektierung, Anpassung und Einführung von PLM-Systemen. Beispiele und Fallstudien für den industriellen Einsatz moderner Informationstechnologien.

Lehrmodule
- Einführung in die PLM-Technologie
- Datenbanktechnologie im Digitalen Produkt
- Objektmanagement
- Objektklassifikation
- Objektidentifikation mit Sachnummernsystem
- Prozess- Kooperationsmanagement
- Workflow Management
- Schnittstellen im Digitalen Produkt
- Enterprises Application Integration
Lecture notesDidaktisches Konzept/ Unterlagen/ Kosten
Die Durchführung der Lehrveranstaltung erfolgt gemischt mit Vorlesungs- und Übungsanteilen anhand von Praxisbeispielen.
Handouts für Inhalt und Case; zT. E-learning; Kosten Fr.20.--
Prerequisites / NoticeVoraussetzungen
Empfohlen:
Informatik II; Fokus-Projekt; Freude an Informationstechnologien

Testat/ Kredit-Bedingungen / Prüfung
Erfolgreiche Durchführung von Übungen in Teams
Mündliche Prüfung 30 Minuten, theoretisch und anhand konkreter Problemstellungen
151-0361-00LStructural Analysis with FEM Information W4 credits3GG. Kress
AbstractThe class material includes mathematical ancillary concepts, derivation of element equations, boundary conditions, numerical integration, compilation of the system’s equations, solution methods, static and eigenvalue problems, sub-structuring techniques, degree-of-freedom coupling and non-linear simulation of progressing damage. ANSYS and also a MATLAB coded learning program are utilized.
ObjectiveWith regard to structural analysis and simulation of Production processes, the theoretical background as well as practical abilities of an engineering analyst shall be transferred. The emphasis on optimization methods reflects the trend that computational methods are not only used to confirm the behaviour of exissting designs anymore but take an increasingliy active and creative role in the product development.
Content1. Direct Method for Derivation of Finite Elements
2. Variational Method for Derivation of Finite-Elements
3. Isoparametric Coordinate Transformation
4. Numerical Integration and Integration Errors
5. System equations Assembly
6. Boundary Conditions and Degree-of-Freedom Constraints
7. System equations Solution and Substructuring
8. Eigenvalue Problem Solution with Vector Iteration
9. Beam Elements and Locking Effect
10. Introduction to Application Software
Lecture notesScript and handouts are provided in class and can also be down-loaded from:
Link
LiteratureNo textbooks required.
151-0940-00LModelling and Mathematical Methods in Process and Chemical Engineering Information W4 credits3GM. Mazzotti
AbstractStudy of the non-numerical solution of systems of ordinary differential equations and first order partial differential equations, with application to chemical kinetics, simple batch distillation, and chromatography.
ObjectiveStudy of the non-numerical solution of systems of ordinary differential equations and first order partial differential equations, with application to chemical kinetics, simple batch distillation, and chromatography.
ContentDevelopment of mathematical models in process and chemical engineering, particularly for chemical kinetics, batch distillation, and chromatography. Study of systems of ordinary differential equations (ODEs), their stability, and their qualitative analysis. Study of single first order partial differential equation (PDE) in space and time, using the method of characteristics. Application of the theory of ODEs to population dynamics, chemical kinetics (Belousov-Zhabotinsky reaction), and simple batch distillation (residue curve maps). Application of the method of characteristic to chromatography.
Lecture notesno skript
LiteratureA. Varma, M. Morbidelli, "Mathematical methods in chemical engineering," Oxford University Press (1997)
H.K. Rhee, R. Aris, N.R. Amundson, "First-order partial differential equations. Vol. 1," Dover Publications, New York (1986)
R. Aris, "Mathematical modeling: A chemical engineer’s perspective," Academic Press, San Diego (1999)
151-0119-00LMolecular Fluid MechanicsW1 credit1GS. Schlamp, T. Rösgen
AbstractTheory, applications, and simulation methods of fluids away from the continuum limit. The focus is on rarefied gases, but applications to micro-fluid mechanics will also be addressed.
ObjectiveFluids are usually treated in the continuum limit. For example, this assumption underlies the Navier-Stokes equations. For certain applications, this is not appropriate; when either the gas becomes so dilute that the molecules' mean-free path is comparable to external length scales (such as for hypersonic flight in the upper atmosphere), or when the external length scales become so small as to approach the molecular length scales (microfluid mechanics).

Students will learn:
- Relationship between the molecular nature of fluids and macroscopic quantities
- Underlying assumptions and approximations of continuum fluid mechanics in general and the Navier-Stokes equation in particular
- Theoretical and numerical approaches to treat non-continuum flows
ContentMolecular description of matter: distribution functions, discrete-velocity gases, relation to macroscopic quantities

Kinetic theory: free-path theory, internal degrees of freedom.

Boltzmann equation: BBGKY hierarchy and closure, H theorem, Euler equations, Chapman-Enskog procedure, free-molecule flows.

Collisionless and transitional flows

Direct simulation Monte Carlo methods

Hypersonics

Applications
Lecture notesThe class will follow the text book fairly closely.
LiteratureText book:
T. I. Gombosi , Gaskinetic Theory, Cambridge University Press, 2008.

Suggested literature:
Ching Shen, Rarefied Gas Dynamics: Fundamentals, Simulations and Micro Flows (Heat and Mass Transfer), Springer, Berlin, 2005.
151-0980-00LBiofluiddynamicsW4 credits2V + 1UD. Obrist, P. Jenny
AbstractIntroduction to the fluid dynamics of the human body and the modeling of physiological flow processes (biomedical fluid dynamics).
ObjectiveA basic understanding of fluid dynamical processes in the human body. Knowledge of the basic concepts of fluid dynamics and the ability to apply these concepts appropriately.
ContentThis lecture is an introduction to the fluid dynamics of the human body (biomedical fluid dynamics). For selected topics of human physiology, we introduce fundamental concepts of fluid dynamics (e.g., creeping flow, incompressible flow, flow in porous media, flow with particles, fluid-structure interaction) and use them to model physiological flow processes. The list of studied topics includes the cardiovascular system and related diseases, blood rheology, microcirculation, respiratory fluid dynamics and fluid dynamics of the inner ear.
Lecture notesLecture notes are provided electronically.
LiteratureA list of books on selected topics of biofluiddynamics can be found on the course web page.
151-0104-00LUncertainty Quantification for Engineering & Life Sciences Restricted registration - show details
Does not take place this semester.
Number of participants limited to 40.
W4 credits3GP. Koumoutsakos
AbstractQuantification of uncertainties in computational models pertaining to applications in engineering and life sciences. Exploitation of massively available data to develop computational models with quantifiable predictive capabilities. Applications of Uncertainty Quantification and Propagation to problems in mechanics, control, systems and cell biology.
ObjectiveThe course will teach fundamental concept of Uncertainty Quantification and Propagation (UQ+P) for computational models of systems in Engineering and Life Sciences. Emphasis will be placed on practical and computational aspects of UQ+P including the implementation of relevant algorithms in multicore architectures.
ContentTopics that will be covered include: Uncertainty quantification under
parametric and non-parametric modelling uncertainty, Bayesian inference with model class assessment, Markov Chain Monte Carlo simulation, prior and posterior reliability analysis.
Lecture notesThe class will be largely based on the book: Data Analysis: A Bayesian Tutorial by Devinderjit Sivia as well as on class notes and related literature that will be distributed in class.
Literature1. Data Analysis: A Bayesian Tutorial by Devinderjit Sivia
2. Probability Theory: The Logic of Science by E. T. Jaynes
3. Class Notes
Prerequisites / NoticeFundamentals of Probability, Fundamentals of Computational Modeling
227-0116-00LVLSI I: From Architectures to VLSI Circuits and FPGAs Information W7 credits5GH. Kaeslin, N. Felber
AbstractThis first course in a series that extends over three consecutive terms is concerned with tailoring algorithms and with devising high performance hardware architectures for their implementation as ASIC or with FPGAs. The focus is on front end design using HDLs and automatic synthesis for producing industrial-quality circuits.
ObjectiveUnderstand Very-Large-Scale Integrated Circuits (VLSI chips), Application-Specific Integrated Circuits (ASIC), and Field-Programmable Gate-Arrays (FPGA). Know their organization and be able to identify suitable application areas. Become fluent in front-end design from architectural conception to gate-level netlists. How to model digital circuits with VHDL or SystemVerilog. How to ensure they behave as expected with the aid of simulation, testbenches, and assertions. How to take advantage of automatic synthesis tools to produce industrial-quality VLSI and FPGA circuits. Gain practical experience with the hardware description language VHDL and with industrial Electronic Design Automation (EDA) tools.
ContentThis course is concerned with system-level issues of VLSI design and FPGA implementations. Topics include:
- Overview on design methodologies and fabrication depths.
- Levels of abstraction for circuit modeling.
- Organization and configuration of commercial field-programmable components.
- VLSI and FPGA design flows.
- Dedicated and general purpose architectures compared.
- How to obtain an architecture for a given processing algorithm.
- Meeting throughput, area, and power goals by way of architectural transformations.
- Hardware Description Languages (HDL) and the underlying concepts.
- VHDL and SystemVerilog compared.
- VHDL (IEEE standard 1076) for simulation and synthesis.
- A suitable nine-valued logic system (IEEE standard 1164).
- Register Transfer Level (RTL) synthesis and its limitations.
- Building blocks of digital VLSI circuits.
- Functional verification techniques and their limitations.
- Modular and largely reusable testbenches.
- Assertion-based verification.
- Synchronous versus asynchronous circuits.
- The case for synchronous circuits.
- Periodic events and the Anceau diagram.
- Case studies, ASICs compared to microprocessors, DSPs, and FPGAs.

During the exercises, students learn how to model digital ICs with VHDL. They write testbenches for simulation purposes and synthesize gate-level netlists for VLSI chips and FPGAs. Only commercial EDA software by leading vendors is being used.
Lecture notesTextbook and all further documents in English.
LiteratureH. Kaeslin: "Top-Down Digital VLSI Design, from Architectures to Gate-Level Circuits and FPGAs", Elsevier, 2014, ISBN 9780128007303.
Prerequisites / NoticePrerequisites:
Basics of digital circuits.

Examination:
In written form following the course semester (spring term). Problems are given in English, answers will be accepted in either English oder German.

Further details:
Link
227-0148-00LVLSI III: Test and Fabrication of VLSI Circuits Information W6 credits4GN. Felber, H. Kaeslin
AbstractThis last course in our VLSI series is concerned with the manufacturing of integrated circuits (IC) in CMOS technology, with defects that may occur during the process, and ---above all--- with the methods and tools for detecting design flaws and fabrication defects.
ObjectiveKnow how to apply methods, software tools and equipment for designing testable VLSI circuits, for testing fabricated ICs, and for physical analysis in the occurrence of defective parts. A basic understanding of modern semiconductor technologies.
ContentThis final course in a series of three focusses on manufacturing, testing, physical analysis, and packaging of VLSI circuits. Future prospects of micro- and nanoelectronics are also being discussed. Topics include:
- Effects of fabrication defects.
- Abstraction from physical to transistor- and gate-level fault models.
- Fault grading in the occurrence of large ASICs.
- Generation of efficient test vector sets.
- Enhancement of testability with built-in self test.
- Organisation and application of automated test equipment.
- Physical analysis of devices.
- Packaging problems and solutions.
- Today's nanometer CMOS fabrication processes (HKMG).
- Optical and post optical Photolithography.
- Potential alternatives to CMOS technology and MOSFET devices.
- Evolution paths for design methodology.
- Industrial roadmaps for the future evolution of semiconductor technology (ITRS).

Exercises teach students how to use CAE/CAD software and automated equipment for testing ASICs after fabrication. Students that have submitted a design for manufacturing at the end of the 7th term do so on their own circuits. Physical analysis methods with professional equipment (AFM, DLTS) complement this training.
Lecture notesEnglish lecture notes.

All written documents in English.
Prerequisites / NoticePrerequisites:
Basics of digital design.

Further details:
Link
227-0418-00LAlgebra and Error Correcting Codes Information W6 credits4GH.‑A. Loeliger
AbstractThe course is an introduction to error correcting codes covering both classical algebraic codes and modern iterative decoding. The course is also an introduction to "abstract" algebra and some of its applications in coding and signal processing.
ObjectiveThe course is an introduction to error correcting codes covering both classical algebraic codes and modern iterative decoding. The course is also an introduction to "abstract" algebra and some of its applications in coding and signal processing.
ContentCoding: coding and modulation, linear codes, Hamming space codes, Euclidean space codes, trellises and Viterbi decoding, convolutional codes, factor graphs and message passing algorithms, low-density parity check codes, turbo codes, polar codes, Reed-Solomon codes.
Algebra: groups, rings, homomorphisms, ideals, fields, finite fields, vector spaces, polynomials, Chinese Remainder Theorem.
Lecture notesLecture Notes (english)
227-0420-00LInformation Theory II Information W6 credits2V + 2US. M. Moser
AbstractThis course builds on Information Theory I. It introduces additional topics in single-user communication, connections between Information Theory and Statistics, and Network Information Theory.
ObjectiveThe course has two objectives: to introduce the students to the key information theoretic results that underlay the design of communication systems and to equip the students with the tools that are needed to conduct research in Information Theory.
ContentDifferential entropy, maximum entropy, the Gaussian channel and water filling, the entropy-power inequality, Sanov's Theorem, Fisher information, the broadcast channel, the multiple-access channel, Slepian-Wolf coding, and the Gelfand-Pinsker problem.
Lecture notesn/a
LiteratureT.M. Cover and J.A. Thomas, Elements of Information Theory, second edition, Wiley 2006
227-0434-00LHarmonic Analysis: Theory and Applications in Advanced Signal Processing Information W6 credits2V + 2UH. Bölcskei
AbstractThis course is an introduction to the field of applied harmonic analysis with emphasis on applications in signal processing such as transform coding, inverse problems, imaging, signal recovery, and inpainting. We will consider theoretical, applied, and algorithmic aspects.
ObjectiveThis course is an introduction to the field of applied harmonic analysis with emphasis on applications in signal processing such as transform coding, inverse problems, imaging, signal recovery, and inpainting. We will consider theoretical, applied, and algorithmic aspects.
ContentFrame theory: Frames in finite-dimensional spaces, frames for Hilbert spaces, sampling theorems as frame expansions

Spectrum-blind sampling: Sampling of multi-band signals with known support set, density results by Beurling and Landau, unknown support sets, multi-coset sampling, the modulated wideband converter, reconstruction algorithms

Sparse signals and compressed sensing: Uncertainty principles, recovery of sparse signals with unknown support set, recovery of sparsely corrupted signals, orthogonal matching pursuit, basis pursuit, the multiple measurement vector problem

High-dimensional data and dimension reduction: Random projections, the Johnson-Lindenstrauss Lemma, the Restricted Isometry Property, concentration inequalities, covering numbers, Kashin widths
Lecture notesLecture notes, problem sets with documented solutions.
LiteratureS. Mallat, ''A wavelet tour of signal processing: The sparse way'', 3rd ed., Elsevier, 2009

I. Daubechies, ''Ten lectures on wavelets'', SIAM, 1992

O. Christensen, ''An introduction to frames and Riesz bases'', Birkhäuser, 2003

K. Gröchenig, ''Foundations of time-frequency analysis'', Springer, 2001

M. Elad, ''Sparse and redundant representations -- From theory to applications in signal and image processing'', Springer, 2010
Prerequisites / NoticeThe course is heavy on linear algebra, operator theory, and functional analysis. A solid background in these areas is beneficial. We will, however, try to bring everybody on the same page in terms of the mathematical background required, mostly through reviews of the mathematical basics in the discussion sessions. Moreover, the lecture notes contain detailed material on the advanced mathematical concepts used in the course. If you are unsure about the prerequisites, please contact C. Aubel or H. Bölcskei.
227-0104-00LCommunication and Detection Theory Information W6 credits4GS. M. Moser
AbstractThis introduction to Detection and Communication Theory offers a glimpse at analog communication, but mainly focuses on the foundations of modern digital communications. Topics include the geometry of the space of energy-limited signals; the baseband representation of passband signals, spectral efficiency and the Nyquist Criterion; the power and power spectral density of PAM and QAM; hypothes
ObjectiveThis is an introductory class to the field of wired and wireless communication. It offers a glimpse at classical analog modulation (AM, FM), but mainly focuses on aspects of modern digital communication, including modulation schemes, spectral efficiency, power budget analysis, block and convolu- tional codes, receiver design, and multi- accessing schemes such as TDMA, FDMA and Spread Spectrum.
Content- Analog Modulation (AM, FM, DSB).
- A block diagram of a digital cellular mobile phone system.
- The Nyquist Criterion for no ISI and the Matched Filter.
- Counting bits/dimension, bits/sec, bits/sec/Hz in base-band.
- Power Spectral Density, and the "energy- per-bit" parameter.
- Passband communication (QAM).
- Detection in white Gaussian noise.
- Sufficient statistics.
- The Chernoff and Bhattacharyya bounds.
- Signals as a vector space: continuous time Inner products and the Gram-Schmidt algorithm.
- Block and Convolutional Codes for the Gaussian channel.
- Multi-accessing schemes such as FDMA, TDMA, and CDMA
Lecture notesn/a
LiteratureA. Lapidoth, A Foundation in Digital Communication, Cambridge University Press 2009
227-0120-00LCommunication Networks Information W6 credits4GB. Plattner, B. L. H. Ager, P. Georgopoulos, K. A. Hummel, L. Vanbever
AbstractThe students will understand the fundamental concepts of communication networks, with a focus on computer networking. They will learn to identify relevant mechanisms that are used in networks, and will see a reasonable set of examples implementing such mechanisms, both as seen from an abstract perspective and with hands-on, practical experience.
ObjectiveThe students will understand the fundamental concepts of communication networks, with a focus on computer networking. They will learn to identify relevant mechanisms that are used to networks work, and will see a reasonable set of examples implementing such mechanisms, both as seen from an abstract perspective and with hands-on, practical experience.
Prerequisites / NoticePrerequisites: A layered model of communication systems (represented by the OSI Reference Model) has previously been introduced.
227-0158-00LSemiconductor Transport Theory and Monte Carlo Device Simulation Information W4 credits2V + 1UF. Bufler, A. Schenk
AbstractThe first part deals with semiconductor transport theory including the necessary quantum mechanics.
In the second part, the Boltzmann equation is solved with the stochastic methods of Monte Carlo simulation.
The exercises address also TCAD simulations of MOSFETs. Thus the topics include theoretical physics,
numerics and practical applications.
ObjectiveOn the one hand, the link between microscopic physics and its concrete application in device simulation is established; on the other hand, emphasis is also laid on the presentation of the numerical techniques involved.
ContentQuantum theoretical foundations I (state vectors, Schroedinger and Heisenberg picture). Band structure (Bloch theorem, one dimensional periodic potential, density of states). Pseudopotential theory (crystal symmetries, reciprocal lattice, Brillouin zone).
Semiclassical transport theory (Boltzmann transport equation (BTE), scattering processes, linear transport).<br>
Monte Carlo method (Monte Carlo simulation as solution method of the BTE, algorithm, expectation values).<br>
Implementational aspects of the Monte Carlo algorithm (discretization of the Brillouin zone, self-scattering according to Rees, acceptance- rejection method etc.). Bulk Monte Carlo simulation (velocity-field characteristics, particle generation, energy distributions, transport parameters). Monte Carlo device simulation (ohmic boundary conditions, MOSFET simulation).
Quantum theoretical foundations II (limits of semiclassical transport theory, quantum mechanical derivation of the BTE, Markov-Limes).
Lecture notesLecture notes (in German)
227-0159-00LQuantum Transport in Nanoscale Devices Information W6 credits2V + 2UM. Luisier
AbstractThis class offers an introduction into quantum transport theory, a rigorous approach to electron transport at the nanoscale. It covers different topics such as bandstructure, Wave Function and Non-equilibrium Green's Function formalisms, and electron interactions with their environment. Matlab exercises accompany the lectures where students learn how to develop their own transport simulator.
ObjectiveThe continuous scaling of electronic devices has given rise to structures whose dimensions do not exceed a few atomic layers. At this size, electrons do not behave as particle any more, but as propagating waves and the classical representation of electron transport as the sum of drift-diffusion processes fails. The purpose of this class is to explore and understand the displacement of electrons through nanoscale device structures based on state-of-the-art quantum transport methods and to get familiar with the underlying equations by developing his own nanoelectronic device simulator.
ContentThe following topics will be addressed:
- Introduction to quantum transport modeling
- Bandstructure representation and effective mass approximation
- Open vs closed boundary conditions to the Schrödinger equation
- Comparison of the Wave Function and Non-equilibrium Green's Function formalisms as solution to the Schrödinger equation
- Self-consistent Schödinger-Poisson simulations
- Quantum transport simulations of resonant tunneling diodes and quantum well nano-transistors
- Top-of-the-barrier simulation approach to nano-transistor
- Electron interactions with their environment (phonon, roughness, impurity,...)
- Multi-band transport models
Lecture notesLecture slides are distributed every week and can be found at
Link
LiteratureRecommended textbook: "Electronic Transport in Mesoscopic Systems", Supriyo Datta, Cambridge Studies in Semiconductor Physics and Microelectronic Engineering, 1997
Prerequisites / NoticeBasic knowledge of semiconductor device physics and quantum mechanics
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