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  • 3.00 Credits

    Spectral estimation including nonparametric methods such as Welch and Blackman-Tukey; modern parametric methods for AR, MA and ARMA spectra including Yule-Walker and Levinson-Durbin. Parametric line spectral subspace methods including MUSIC and ESPRIT. Filterbank and spatial methods such as beamforming. Prerequisites: EE 3220, 4220 or equivalent.
  • 3.00 Credits

    Introduces students to advanced aspects of image processing (IP), using specific applications to demonstrate these principles. Concepts such as medical imaging; color IP; wavelets and multiresolution IP; image compression; morphological IP; image segmentation, representation, description and understanding are covered. Prerequisites: EE 4530.
  • 3.00 Credits

    Adaptive filtering including eigenanalysis, low-rank modeling, Wiener filters, linear prediction, steepest descent methods, least mean-squares and recursive least squares methods, adaptive beamforming. Performance, convergence, and stability issues. Realization techniques. Prerequisites: EE 4220.
  • 3.00 Credits

    Introduces students to both fundamental and advanced aspects of object and pattern recognition, using specific applications to demonstrate these principles. Concepts such as Bayesian, maximum-likelihood, principal components, nonparametric, linear discriminant, multi-layer neural networks, etc., and the trade-offs and appropriateness of classification techniques are covered. Prerequisite: EE 4220.
  • 3.00 Credits

    Fundamental and advanced topics in identification of system models from measured data. A variety of model structures are studied such as ARX, ARMAX, and State Space. Both non-parametric and parametric identification techniques are investigated with applications to real world systems and data. Experiment design and model validation are also examined. Prerequisites: EE 4220.
  • 3.00 Credits

    This course introduces fundamental aspects of practical digital image formation, using specific applications to demonstrate these principles. Standard CCD and CMOS cameras (both still and video) and standard camera lens systems are assumed. Prerequisite: EE 3220 or graduate standing.
  • 2.00 - 6.00 Credits

    Design of transmission lines and distribution systems. Coordination studies. System stability studies, load distribution and dispatching. System interconnections. Correlation of machines and transmission systems. Prerequisite: EE 3510.
  • 3.00 Credits

    Power quality is gaining increasing interests among both electric utilities and end users of electric power. In this course, a comprehensive introduction to the electric power quality engineering will be given to prepare you for the incoming power quality disturbances and causes, voltage sag and interruptions, electric transient, and harmonics. Prerequisites: EE 3510 or graduate standing.
  • 3.00 Credits

    Topics of modern control theory. State variables review. Calculus of variations with applications to the deviation of complex system state equations and functional minimization of fixed and variable-end point problems. Pontryagin's minimum principle and its application to the general optimal control problem. Prerequisite: EE 4620.Course discontinued Summer 2001 as part of the Old Course Cleanup project.
  • 3.00 Credits

    Introduction to the analysis and synthesis of sample data control systems. Application of digital computing devices to control systems. Term paper on special problems. Prerequisite: EE 4620.