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Course Outline
Peter Dannenmann, Georg Fries, Karin Grslund, Patrick Metzler, Michael Schmidt, Andreas Zinnen
Dr. Peter Dannenmann Modelling and Simulation using MATLAB 2
Course Outline
Chapter 1: Modelling and Simulation (starting April 22nd, 2014)
Background information on the applications of simulation techniques
Classification of simulation systems
Basic simulation and modelling techniques
The Model Development Life Cycle
Dr. Georg Fries Modelling and Simulation using MATLAB 3
Course Outline
Chapter 2: Introduction to MATLAB Concepts (starting April 29th, 2014)
The MATLAB User Interface Commands Plotting Numbers Variables, Arrays and Matrices Scripts and Functions Control Flow Examples
Dr. Karin Grslund Modelling and Simulation using MATLAB 4
Course Outline
Chapter 3: Modelling a Business Case (starting May 6th, 2014)
Overview on Modelling Business Cases
Workshop on Design Thinking
Calculating a Business Case
Dr. Patrick Metzler Modelling and Simulation using MATLAB 5
Course Outline
Chapter 4: Methods to Solve Formal Problems (starting May 13th, 2014)
Toolbox for Solving Formal Problems Analogies Definitions Divide and Conquer Exchange of Given and Looked For Plausibility Tests
Brute Force Least Squares Monte Carlo
Dr. Michael Schmidt Modelling and Simulation using MATLAB 6
Course Outline
Chapter 5: Knowledge Management (starting May 20th, 2014)
Knowledge is THE critical factor for successful technological developments.
In simulation and modeling experts need to share their knowledge to achieve synergies. This means explicating tacit knowledge.
As it is a most success-critical resource, we need to find out how we can make knowledge available to the development processes in simulation and modeling.
Modelling and Simulation using MATLAB 7
Elective Chapters Introduction to Simulink Statistics for Image Processing
and Machine Learning
Business Case Applications Instance Based Machine
Learning in a Nutshell
Modelling a Water-Treatment Plant
Control Engineering Applications
Applications of Knowledge Management Techniques
Image Processing in a Nutshell
Course Outline
Dr. Peter Dannenmann Modelling and Simulation using MATLAB 8
Course Outline
Application Chapter: Introduction to Simulink
Required Previous Chapters: Chapters 1 to 5 Simulinks concept of modelling mathematical
equations: building blocks representing operations and
connections representing data flow
Introduction to Simulinks libraries Handling signals, combining signals to busses Numerical integration in Simulink Hierarchical structuring of simulation models,
modelling subsystems as building blocks of their own
Dr. Georg Fries Modelling and Simulation using MATLAB 9
Course Outline
Application Chapter: Statistics for Image Processing and Machine Learning
Required Previous Chapters: Chapters 1 to 5 Random number generation Bayes' theorem Probability density function
Cumulative distribution function Binomial distribution Gaussian distribution Mixture of Gaussian
Histogram processing Bins, equalization, matching Luminance and chrominance
enhancement
10 Dr. Andreas Zinnen Modelling and Simulation using MATLAB
Required Previous Chapters: Statistics for Image Processing and Machine Learning
k-means clustering k-nearest neighbours
Regression analysis/classification Density estimation
Novelty detection using KDE Nadaraya Watson and Silverman
Cross validation Model evaluation
Course Outline
Application Chapter: Instance Based Machine Learning in a Nutshell
Dr. Peter Dannenmann Modelling and Simulation using MATLAB 11
Course Outline
Application Chapter: Modelling a Water Treatment Plant
Required Previous Chapters: Introduction to Simulink
Parameters for describing water quality Subsystems of a Water Treatment Plant
Grit chamber, Coagulation basin, Sedimentation basin, Grit filter, Activated carbon filter, UV-disinfection
Mathematical models for describing the subsystems of a Water Treatment plant
Techniques for describing the water parameters and for implementing the mathematical Models
Modelling the single subsystems in Simulink and integrating the complete model
Dr. Patrick Metzler Modelling and Simulation using MATLAB 12
Course Outline
Application Chapter: Control Engineering Applications
Required Previous Chapters: Introduction to Simulink Feed Forward Control, Feed Back Control
and Logical Control Empirical Setup of Controller parameters
Ziegler Nichols Chien Hrons Reswick
Speed Control of a NXT Robot Drive Position Control of a NXT Robot Drive Distance Control of a NXT Robot
Dr. Georg Fries Modelling and Simulation using MATLAB 13
Course Outline
Application Chapter: Image Processing in a Nutshell
Required Previous Chapters: Statistics for Image Processing and Machine Learning
Intensity Transformation Image Negatives, Log Transformations Contrast stretching
Spatial Filtering Neighbourhood Filter masks Smoothing, Sharpening, Unsharp Masking Image Enhancement
Examples