11194 - Signal Processing and Optimization Methods in Data Mining Modulübersicht

Module Number: 11194 - module is no longer offered from WS 2020/21
Module Title:Signal Processing and Optimization Methods in Data Mining
  Signalverarbeitung und Optimierungsmethoden für Data Mining
Department: Faculty 3 - Mechanical Engineering, Electrical and Energy Systems
Responsible Staff Member:
  • Prof. Dr.-Ing. Schwarz, Harald
Language of Teaching / Examination:English
Duration:1 semester
Frequency of Offer: Every winter semester
Credits: 6
Learning Outcome:Students will get detailed knowledge about signal processing issues and notions of optimization methods, with practical examples and exercises.
In the optimization part students will learn foundations of optimization methods and their numerical application in engineering. They will be skilled to optimize various types of practical industrial problems.
Contents:The first part of the course introduces foundations of signal processing methods in electrical power engineering. Introducing lectures provide ideas of discrete representations of continuous signal with basic functions and signal orthogonal projection. Next stage of the course concerns continuous representations of deterministic signals. Introduced definitions allow passing into nonparametric time-frequency representations. Then, follow the time-scale representations with wavelets. Backgrounds of statistical signal processing are introduced with outlined parameter estimation, optimal filtering, linear modeling and estimation. Finally, various methods of parametric spectrum estimation are outlined. Examples of application in electrical engineering are presented throughout the course.
Recommended Prerequisites:Courses on Algebra and Analysis
Mandatory Prerequisites:None
Forms of Teaching and Proportion:
  • Lecture / 4 Hours per Week per Semester
  • Self organised studies / 120 Hours
Teaching Materials and Literature:
  • S. Haykin, B. Van Veen – Signals and Systems, John Wiley & Sons, Inc., 1999, C.W. Therrien – Discrete Random Signals and Statistical Signal Processing, Englewood Cliffs, Prentice Hall, 1992, web based lecture script
  • K.P. Chong, S.H. Zak: An Introduction to Optimization, 2nd edition, New York, John Wiley, 2001, J.F. Bonnans: Numerical optimization: theoretical and practical aspects, Springer-Verlag, 2003, M. Asghar Bhatti: Practical Optimization Methods, Berlin, Springer-Verlag 2000
Module Examination:Final Module Examination (MAP)
Assessment Mode for Module Examination:
  • Written examination, 90 minutes
Evaluation of Module Examination:Performance Verification – graded
Limited Number of Participants:None
Part of the Study Programme:
  • no assignment
Remarks:The lecture will be not offered in winter semester 2017/18.
Module Components:
  • Signal Processing and Optimization Methods in Data Mining (lecture)
Components to be offered in the Current Semester:
  • no assignment
Follow-up Module/s: Phase-out module since: 04.10.2017
  • without Follow-up Module/s