Search result: Catalogue data in Spring Semester 2020
|Electrical Engineering and Information Technology Bachelor|
|Bachelor Studies (Programme Regulations 2018)|
|Examination Block 2|
|227-0013-00L||Computer Engineering||O||4 credits||2V + 1U + 1P||L. Thiele|
|Abstract||The 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.|
|Objective||Logical 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.|
|Content||Structures 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 notes||Material for practical training, copies of transparencies.|
|Literature||D.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 / Notice||Prerequisites: Programming skills in high level language, knowledge of digital design.|
|227-0046-10L||Signals and Systems II||O||4 credits||2V + 2U||J. Lygeros|
|Abstract||Continuous and discrete time linear system theory, state space methods, frequency domain methods, controllability, observability, stability.|
|Objective||Introduction to basic concepts of system theory.|
|Content||Modeling 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 notes||Copy of transparencies|
K.J. Astrom and R. Murray, "Feedback Systems: An Introduction for Scientists and Engineers", Princeton University Press 2009
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