Signal Processing and Control Certificate

Transform domain and state space representations of linear systems. System response, system stability, root locus method, frequency response-based design and state space system analysis and design.

Systematically introduces concepts and analytical tools required to abstract engineering problems from real-world applications, and to simulate and analyze such problems. Main topics include the modeling of dynamical systems using ordinary differential equations, state-space representations, input-output equations and transfer functions, the analysis of system response, and a brief introduction to control systems including PID controllers design.

Digital Signal Processing (DSP) continues to evolve and play a central role in modern electronics and electromechanics systems. Many systems today, such as HDTV, mp3 players, Internet audio and video, Voice over IP, digital communications, vehicular controls, machine intelligence, etc., use powerful DSP concepts as their foundations. DSP is a logical extension of Signals and Systems in which a comprehensive view of discrete-time systems is taken. The course content succinctly stated is an introduction to modern digital signal processing theory and techniques. This includes discrete time signals and systems, sampling theorem, Z-transform, frequency analysis of signals and systems, discrete Fourier transform, fast Fourier transform algorithms, digital filter design, and other topics (e.g. multi-rate signal processing, wavelets, linear prediction).

Mathematical principles of computer vision and image analysis. Binary image processing with techniques of mathematical morphology, grey level image processing with various filters, color fundamentals and texture representation and recognition are discussed. Advanced topics such as content-based image retrieval, shape form X-techniques, 2D/3D object recognition and matching are also discussed.