Difference between revisions of "CEM"

From Maxwell
Jump to: navigation, search
Line 16: Line 16:
  
 
=== Course Description ===
 
=== Course Description ===
Introduction to fundamental ideas and techniques of stochastic analysis and modeling. Random variables, expectation and conditional expectation, joint distributions, covariance, moment generating function, central limit theorem, weak and strong laws of large numbers, discrete time stochastic processes, stationarity, power spectral densities and the Wiener-Khinchine theorem, Gaussian processes, Poisson processes, Brownian motion. The course develops applications in selected areas such as signal processing (Wiener filter), information theory, genetics, queuing and waiting line theory, and finance.
+
Introduction to fundamental ideas and techniques of finite element method and modeling in electromagnetics. Basics of electromagnetics, equations of static magnetic, electrostatic, eddy current and time dependent problems, Helmholtz-equation, basic of finite element method, nodal and edge shape functions, boundary conditions, mesh operations. The course  Random variables, expectation and conditional expectation, joint distributions, covariance, moment generating function, central limit theorem, weak and strong laws of large numbers, discrete time stochastic processes, stationarity, power spectral densities and the Wiener-Khinchine theorem, Gaussian processes, Poisson processes, Brownian motion. The course solves problems in selected areas such as fuel injection solenoid, eddy current brake, permanent magnet motor and .

Revision as of 19:46, 28 January 2019

Introduction to Computational Electromagnetics

Instructors

  • Dániel Marcsa (lecturer)
  • Lectures: Monday, 14:50 - 16:25 (D201), 16:30 - 17:15 (D105)
  • Office hours: by request

Teaching Assistants

  • -
  • Office hours: -.

Course Description

Introduction to fundamental ideas and techniques of finite element method and modeling in electromagnetics. Basics of electromagnetics, equations of static magnetic, electrostatic, eddy current and time dependent problems, Helmholtz-equation, basic of finite element method, nodal and edge shape functions, boundary conditions, mesh operations. The course Random variables, expectation and conditional expectation, joint distributions, covariance, moment generating function, central limit theorem, weak and strong laws of large numbers, discrete time stochastic processes, stationarity, power spectral densities and the Wiener-Khinchine theorem, Gaussian processes, Poisson processes, Brownian motion. The course solves problems in selected areas such as fuel injection solenoid, eddy current brake, permanent magnet motor and .