Lectures

IT Laboratory Mechanical Engineering

Link to the IT Laboratory (Ilias Login required)

Bachelor, Master Theses and Student Research Projects

Please contact Prof. Niggemann for current topics or check this Link (Ilias login required)

Lectures Fall

Bachelor Engineering Science:
Discrete Control Systems:
1. Boolean Algebra, PLC Programming using boolean formulas.
2. Finite State Machines FSM, Timed FSMs, Probabilistic FSMs.
3. Analysis of FSMs, Observation and Diagnosis of FSMs

Bachelor Maschinenbau:
Informatik I:
1. Einführung in die Programmierung in C, Listen, Arrays, Strukturen, Funktionen, Pointer.
2. Einfache Algorithmen in C, Sortieren, Suchen, Graphen.
3. Einführung in Skriptsprachen am Beispiel Python und Matlab

Informatik II:
1. Objekt-orientierte Programmierung in Java, Klassen, Komponenten, Kapselung, Vererbung, Abstraktion, Polymorphie.
2. SW- und Systemmodellierung in UML und SysML

Master Mechatronik:
Methoden der Künstlichen Intelligenz 2:
1. Logikkalküle
2. Diagnosemethoden, heuristische Diagnose, Fallbasierte Diagnose, Modellbasierte Diagnose
3. Rekonfiguration und Planen

ISA-Lecture:
Agenda and Access ISA-Lecture

Lectures Winter

Bachelor Engineering Science:
Programming in C:
1. Introduction to C, Lists, Arrays, Structures, Functions, Pointers.
2. Simple algorithms, Sorting, Searching, Graphs

Master Engineering Science:
Sensors/Actuators:
1. Introduction to sensor/actuators, problems of sensor data analysis.
2. Statistical models for information fusion and data analysis.
3. Machine Learning approaches for data analysis

Lecture Spring

Bachelor Engineering Science:
Introduction to OOP:
1. Object-oriented Programing in Java, Components, Encapsulation, Inheritance, Abstraction, Polymorphism
2. SW and System Modeling in UML and SysML

Master Mechatronik:
Informatik III: Programmierung verteilter Systeme in UNIX.
1. UNIX API, Shell, Prozesse.
2: Inter-Prozess-Kommunikation, Signale, Shared-Memory, Sockets.
3. Deadlock and Deadlock—Vermeidung

Bildverarbeitung:
1. Pixel-orientierte Verfahren
2. Filtermethoden.
3. Bildklassifikation, Neuronale Netze, Convolutional Neural Networks

HSU

Letzte Änderung: 22. November 2021