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This course presents the fundamentals of digital signal processing with particular emphasis on problems in biomedical research and clinical medicine.
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Description
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 physiological data, with examples from cardiology, speech processing, and medical imaging. The labs are done in MATLAB® 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 biological signals processed in the labs
Course content
- Introduction to Biomedical Signal and Image Processing Unlimited
- data acquisition Unlimited
- digital filters Unlimited
- Introduction to Clinical Electrocardiography Unlimited
- The Physiological Basis of the Electrocardiogram Unlimited
- Fourier representation of signals and systems Unlimited
- the discrete Fourier transform Unlimited
- Sampling in time and frequency Unlimited
- Z-transforms Unlimited
- the short-time Fourier transform Unlimited
- linear prediction Unlimited
- image processing Unlimited
- decision systems Unlimited
- Probability primer Unlimited
- Venn diagrams Unlimited
- Image processing 2 Unlimited
- Decision systems 2 – density estimation Unlimited
- Introduction to medical image segmentation Unlimited
- Slides Unlimited
- Slides Unlimited
- Medical image modalities Unlimited
- random signal processing Unlimited
- random signals – basic properties Unlimited
- random signals and linear systems Unlimited
- Lecture slides Unlimited
- blind source separation Unlimited
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