Introduction to Communication, Control, and Signal Processing
Readings
Course Notes: Signals, Systems and Inference
This is a subject that combines topics which have traditionally been taught separately, so there is no single text that is appropriate for it. We will rely largely on the 6.011 lecture notes, Signals, Systems and Inference.
Please note that Chapter 1 is not available on MIT OpenCourseWare.
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CHAPTERS |
NOTES |
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Complete course notes |
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Table of contents |
(PDF) |
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Chapter 1: Introduction |
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Chapter 2: Signals and systems |
(PDF) |
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Chapter 3: Transform representation of signals and linear, time-invariant (LTI) systems |
(PDF) |
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Chapter 4: State-space models |
(PDF) |
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Chapter 5: Properties of LTI state-space models |
(PDF) |
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Chapter 6: State observers and state feedback |
(PDF) |
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Chapter 7: Probabilistic models |
(PDF) |
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Chapter 8: Estimation with minimum mean square error |
(PDF) |
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Chapter 9: Random processes |
(PDF) |
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Chapter 10: Power spectral density |
(PDF) |
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Chapter 11: Wiener filtering |
(PDF) |
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Chapter 12: Pulse amplitude modulation (PAM), quadrature amplitude modulation (QAM) |
(PDF) |
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Chapter 13: Hypothesis testing |
(PDF) |
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Chapter 14: Signal detection |
(PDF) |
Exams
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QUIZ # |
QUIZZES |
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Quiz 1 |
Question booklet (PDF) Answer booklet (PDF) Solutions (PDF) |
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Quiz 2 |
Question booklet (PDF) Answer booklet (PDF) Solutions (PDF) |
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Final exam |
Question booklet (PDF) Answer booklet (PDF) Solutions (PDF) |