Teaching

Graduate: ECE 629 Neural Network @ Fall 20

Covering: Artificial Neural Network, Backpropagation Learning, Optimization Problems, Feedforward and Multistage Networks, Recurrent Network, Backpropagation Through Time Learning, Convergence Analysis, Neural Activation Functions, Learning Theories, Supervised Neural Learning, Unsupervised Neural Learning, etc.


Graduate: ECE 662 Pattern Recognition and Decision Making @ Spring 21 + Spring 20

Covering: Machine Learning Theories, Fundamental Learning Problems and Principles, Mathematical Optimization, Data Analysis, Feature Extraction, Statistical Analysis, Supervised Learning, Unsupervised Learning, Parametric Classifiers, Non-parametric Classifiers, Bayesian Decision Theory, etc.


Undergraduate: ECE 301 Signals and Systems @ Spring 21 + Fall 20 + Fall 19 + Spring 19 + Fall 18

Covering: Fourier Theories and Methods, Convolution, Signal Manipulation, Engineering Modeling, System Modeling, Model Simulation, Time-domain Analysis, Frequency-domain Analysis, Complex System Analysis, Filtering, Transfer Function, Laplace Transform, Z Transform, State Space Analysis, etc.