Electrical Engineering and Computer Science
Principles of Digital Communications I
These video lectures are from the Fall 2003 offering of this course.
Lecture 1: Introduction
Lecture 2: Discrete Source Encoding
Lecture 3: Memory-less Sources
Lecture 4: Entropy and Asymptotic Equipartition Property
Lecture 5: Markov Sources
Lecture 6: Quantization
Lecture 7: High Rate Quantizers and Waveform Encoding
Lecture 8: Measure
Lecture 9: Discrete-Time Fourier Transforms
Lecture 10: Degrees of Freedom
Lecture 11: Signal Space
Lecture 12: Nyquist Theory
Lecture 13: Random Processes
Lecture 14: Jointly Gaussian Random Vectors
Lecture 15: Linear Functionals
Lecture 16: Review; Introduction to Detection
Lecture 17: Detection for Random Vectors and Processes
Lecture 18: Theory of Irrelevance
Lecture 19: Baseband Detection
Lecture 20: Introduction of Wireless Communication
Lecture 21: Doppler Spread
Lecture 22: Discrete-Time Baseband Models for Wireless Channels
Lecture 23: Detection for Flat Rayleigh Fading and Incoherent Channels
Lecture 24: Case Study on Code Division Multiple Access
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