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Affiliation
Massachusetts Institute of Technology
Remove constraint Affiliation: Massachusetts Institute of Technology
Keywords
Signal processing
Remove constraint Keywords: Signal processing
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Courseware
This course covers signals, systems and inference in communication, control and signal processing. Topics include input-output and state-space models of linear systems driven by deterministic and random signals; time- and transform-domain representations in discrete and continuous time; and group delay. State feedback and observers. Probabilistic models; stochastic processes, correlation functions, power spectra, spectral factorization. Least-mean square error estimation; Wiener filtering. Hypothesis testing; detection; matched filters.
- Subjects:
- Electronic and Information Engineering|Electrical Engineering
- Keywords:
- Signal processing Signal theory (Telecommunication) System analysis
- Resource Type:
- Courseware
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Courseware
This course covers the fundamentals of signal and system analysis, focusing on representations of discrete-time and continuous-time signals (singularity functions, complex exponentials and geometrics, Fourier representations, Laplace and Z transforms, sampling) and representations of linear, time-invariant systems (difference and differential equations, block diagrams, system functions, poles and zeros, convolution, impulse and step responses, frequency responses). Applications are drawn broadly from engineering and physics, including feedback and control, communications, and signal processing.
- Subjects:
- Electrical Engineering
- Keywords:
- Signal processing System analysis
- Resource Type:
- Courseware
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Courseware
This course presents the fundamentals of digital signal processing with particular emphasis on problems in biomedical research and clinical medicine. 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.
- Subjects:
- Biomedical Engineering and Medical Imaging
- Keywords:
- Biomedical engineering Signal processing Image processing
- Resource Type:
- Courseware