Search result: Catalogue data in Spring Semester 2020

Electrical Engineering and Information Technology Bachelor Information
Bachelor Studies (Programme Regulations 2018)
Examination Blocks
Examination Block 2
NumberTitleTypeECTSHoursLecturers
227-0013-00LComputer Engineering Information Restricted registration - show details O4 credits2V + 1U + 1PL. Thiele
AbstractThe course provides knowledge about structures and models of digital systems, assembler and compiler, control path and data path, pipelining, speculation techniques, superscalar computer architectures, memory hierarchy and virtual memory, operating system, processes and threads.
Learning objectiveLogical and physical structure of computer systems. Introduction to principles in hardware design, datapath and control path, assembler programming, modern architectures (pipelining, speculation techniques, superscalar architectures, multithreading), memory hierarchy and virtual memory, software concepts.
ContentStructures and models of digital systems, abstraction and hierarchy in computer systems, assembler and compiler, control path and data path, pipelining, speculation techniques, superscalar computer architectures, memory hierarchy and virtual memory, operating system, processes and threads.

Theoretical and practical exercises using a simulation-based infrastructure.
Lecture notesMaterial for practical training, copies of transparencies.
LiteratureD.A. Patterson, J.L. Hennessy: Computer Organization and Design: The Hardware/ Software Interface. Morgan Kaufmann Publishers, Inc., San Francisco, ISBN-13: 978-0124077263, 2014.
Prerequisites / NoticePrerequisites: Programming skills in high level language, knowledge of digital design.
227-0046-10LSignals and Systems IIO4 credits2V + 2UJ. Lygeros
AbstractContinuous and discrete time linear system theory, state space methods, frequency domain methods, controllability, observability, stability.
Learning objectiveIntroduction to basic concepts of system theory.
ContentModeling and classification of dynamical systems.

Modeling of linear, time invariant systems by state equations. Solution of state equations by time domain and Laplace methods. Stability, controllability and observability analysis. Frequency domain description, Bode and Nyquist plots. Sampled data and discrete time systems.

Advanced topics: Nonlinear systems, chaos, discrete event systems, hybrid systems.
Lecture notesCopy of transparencies
LiteratureRecommended:
K.J. Astrom and R. Murray, "Feedback Systems: An Introduction for Scientists and Engineers", Princeton University Press 2009

http://www.cds.caltech.edu/~murray/amwiki/
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