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This course covers signals, systems and inference in communication, control and signal processing.
0
English
English [CC]
FREE
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Description
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.
Course content
- Introduction Unlimited
- Transforms Unlimited
- Energy Spectral Density Unlimited
- State-Space Models Unlimited
- State-Space Models Unlimited
- Modal Solution of Undriven CT Unlimited
- Full Modal Solution Unlimited
- Matrix Exponential Unlimited
- Observers for State Estimation Unlimited
- Observers Unlimited
- State Feedback Unlimited
- Probabilistic Models Unlimited
- Vector Picture for First- and Second-Order Statistics Unlimited
- LMMSE Estimation Unlimited
- Normal Equations Unlimited
- Wide-Sense Stationary Processes Unlimited
- LTI Filtering of WSS Processes Unlimited
- Power Spectral Density (PSD) Unlimited
- Einstein-Wiener-Khinchin Theorem Unlimited
- Wiener Filtering Unlimited
- Wiener Filtering Illustrations Unlimited
- Hypothesis Testing Unlimited
- Neyman-Pearson Testing Unlimited
- Signal Detection Unlimited
- Matched Filtering Unlimited
Instructor
Massachusetts Institute of Technology
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