المواد الدراسية
Introduction to knowledge based intelligent systems, Rule based expert systems, Fuzzy expert systems, Connectionist neural networks, learning and adaptation, Support Vector machine, Evolutionary algorithms (genetic algorithm, Particle swarm...
Mathematical description and classification of various signals and systems: introduction to mathematical software packages (e.g. MATLAB), continuous linear time-invariant systems, convolution and correlation, Fourier series and transforms, Laplace...
Course description (catalog)
Quantitative models of imaging systems, spatial domain and frequency domain methods, digital filter design for image enhancement and restoration, edge detection, image denoising, image segmentation, image enhancement,...
PATTERN RECOGNITION
Course Description:
Covers basic concepts of pattern recognition systems, application examples, PDF estimation, maximum likelihood estimation, Bayesian estimation, KNN estimation, parzen windows estimation, expectation...
Covers probability theory, random variables, descriptive statistics, random sampling, statistical intervals and hypothesis testing for a single sample, stochastic processes, spectral characteristics and applications to systems