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Machine Learning
Course Number:   046195
An introductory course on learning systems in the context of signal processing, artificial intelligence and control. Problems of classification, regression and clustering. Neural networks: multi-level perceptrons and radial basis functions. Decision trees. Elements of the learning theory: the Bayesian approach, hypothesis spaces. Dimensionality reduction using principal components. Classification using support vector machines. Reinforcement learning.
Visual and Auditory Systems
Course Number:   046332
Introduction to the physical and physiological bases of visual and auditory communication. Structure and function of the eye and the ear. Physiological mechanisms involved in encoding, processing and transmitting of sensory signals. Spectral analysis of dynamic signals. Automatic gain control in the retina. Image representation in the combined frequency-position space. Statistical characteristics of the signals and psychophysical detection laws. Models for signal processing in the visual system. Image structure and technological aspects (Computer Vision).
Image Processing
Course Number:   048860
Introduction: The human vision system, image sensors, image displays. Image Transforms: 2D-FT, Hadamard, Walsh, SVD and Karhunen Loeve transforms. Image Enhancement: Histogram modification, smoothing and sharpening by filtering techniques. Image Restoration: Correction of de-focusing and movement effects, Wiener filtering. Image Compression: Information preserving techniques, predictive and transform methods. Introduction to image analysis and computer vision.
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