| 2102500* | (1 Credits) | |
| 2102501* | (2 Credits) | |
| 2102503* | Time Series Analysis Data cleansing; down-sampling, up-sampling; correlation analysis; stationarity test; stationary models; maximum likelihood estimation; applications in anomaly detection and forecasting. | (1 Credits) |
| 2102504 | Introduction to Mathematical Analysis Mathematical proofs; basic set theory; the real number system; topology on the real line; sequence and convergence; limit and continuity of functions; vector spaces and linear operators; normed linear spaces; bounded operators; inner-product spaces; orthogonality and orthonormal bases; adjoint operators; applications to electrical engineering topics. | (3 Credits) |
| 2102508* | Optimization Concepts and Applications General setting; formulating optimization problems; overview of problem types; brief introduction to convex programs; applications in engineering; overview of available methods; essential considerations of algorithms; applying optimization softwares to solve common problem types. | (1 Credits) |
| 2102509* | Introduction to Optimization Techniques One-dimensional optimization; line search; unconstrained optimization; gradient descent; Newton method; trust-region; Levenberg-Marquardt; quasi-Newton; conjugate gradient; interior-point methods; methods for solving quadratic programming; constrained optimization; KKT conditions for nonlinear optimizations. | (2 Credits) |
| 2102510* | Linear Programming Standard form; formulating applied problems in LP form; basic feasible solutions; the simplex method; duality and sensitivity analysis; integer linear programming: relaxation, cutting-plane, branch and bound algorithm. | (1 Credits) |
| 2102511* | Optimization Methods for Engineering and Machine Learning Recent applications in engineering and machine learning; first-order methods for large-scale optimization; duality theory; convex optimization algorithms. | (2 Credits) |
| 2102512* | Heuristic Optimization Introduction to optimization; evolutionary and swarm intelligence algorithms; particle swarm optimization; ant colony optimization; genetic algorithm; decision tree; dynamic programming; applications of operations research. | (2 Credits) |
| 2102513* | Basic Image Processing Sampling and resolution; geometric transform; enhancement; restoration. | (1 Credits) |
| 2102514* | Advanced Image Processing Segmentation; morphology; image description and representation; transforms in image processing; filters; applications. | (2 Credits) |
| 2102515* | Digital Video Processing Analog and digital video; video signal analysis; frequency response of the Human Visual System (HVS); video models; two dimensional motion estimation; foundation of video coding; image and video coding standards. | (2 Credits) |
| 2102516* | Adaptive Signal Processing Linear optimal filter, Wiener filter; adaptive filtering, adaptive algorithms (LMS, RLS); frequency-domain adaptive filtering; applications of adaptive signal processing. | (1 Credits) |
| 2102517* | Wavelet Transform Short-time Fourier transform; 1D and 2D wavelet transform; filter banks; Harr, Daubechies and other wavelets; programming examples. | (1 Credits) |
| 2102518* | Neural Networks and Deep Learn ingIntroduction to deep learning; neural networks basics; shallow neural networks; deep neural networks. | (1 Credits) |
| 2102519* | Reinforcement Learning and Applications Overview of reinforcement learning; introductory example: multi-armed bandit problem; Markov decision process; temporal-difference learning; reinforcement learning implementation with cloud technology; engineering applications. | (1 Credits) |
| 2102521* | System Identification Dynamical models; input design; persistent excitation; constrained least-squares; prediction error method; subspace method; model selection and validation. | (2 Credits) |
| 2102523* | Estimation Theory Properties of estimator; asymptotic distribution of estimators; minimum mean-square estimation; maximum likelihood estimation; Fisher information matrix; Cramer-Rao bound; maximum a posteriori estimation; applications on linear additive models. | (2 Credits) |
| 2102571 | Multimedia Communication Multimedia communication system; multimedia compression technology and standards (image, video, audio); multimedia communication protocols; telecommunication Infrastructure and mobile network ecosystem; multimedia communication applications (Internet of Things (IoTs); intelligent transport system (ITS) and autonomous vehicles; smart health, smart surveillance in smart cities; multimedia data analytics. | (3 Credits) |
| 2102575 | Statistical Inference and Modeling Procedures in statistical modeling; supervised learning; unsupervised learning; ensemble learning; regression models; classfication; clustering; model selection; model validation; engineering applications. | (3 Credits) |