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Course Description This course presents the fundamentals of digital signal processing with particular emphasis on problems in detection and recognition signals and images. It covers principles and algorithms for processing both deterministic and random signals. Topics include data acquisition, imaging, filtering, coding, feature extraction, and modeling. The focus of the course is a series of labs that provide practical experience in processing noise data. The labs will done in MATLAB® or Mathcad® during weekly lab sessions that take place in an electronic classroom. Lectures cover signal processing topics relevant to the lab exercises, as well as background on the noise signals processed in the labs. The basis of the course is the similar teaching at the Massachusetts Institute of Technology (ranked in QS World University Rankings-2013 - 1). MIT Course Number HST.582J / 6.555J / 16.456J "Biomedical Signal and Image Processing". MIT course was extended examples of technical areas: problem underwater noise signal detection of moving objects, problem of functional diagnostics of turn-to-turn short circuits in synchronous generator windings.
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