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Statistical Signal Processing

EI70240Specialization in Technology5 ECTSEnglishsummer semesterDepartment Computer Engineering
AI-edited module sheet. Based on the TUMonline module description, edited for readability.Original in TUMonline

What it is about

You learn the fundamentals of probability theory and stochastic processes and apply statistical methods to estimation and decision making. In the end you will be able to understand, evaluate and independently apply and develop mathematical concepts and numerical algorithms of statistical signal processing for communication and data processing applications.

What you will be able to do

  • Understand fundamental concepts of probability and stochastic processes
  • Apply and evaluate estimation procedures (MLE, Bayes, MMSE, LMMSE)
  • Design and analyze recursive estimation procedures (Kalman, Particle filter)
  • Perform and assess statistical hypothesis tests (Neyman-Pearson, ML, MAP, Bayes)
  • Apply selected topics such as confidence analysis, kernel methods and neural networks

What the module consists of

  • VorlesungIntroduction of mathematical concepts and numerical algorithms to selected topics of statistical signal processing
  • Übungen/Case StudiesTransfer of concepts to case studies and applications; deepening through exercises

Teaching method

  • VorlesungenConveying mathematical concepts and algorithms
  • Case Studies / AnwendungsbeispieleDemonstration of the application of the introduced concepts and algorithms
  • ÜbungsaufgabenIndependent investigation and solution of specific questions for deepening
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Official page in TUMonline · Details are not binding.