Lecture 1: Introduction
Lecture 2: What is Information? Probability and Entropy
Lecture 3: Lossless Compression
Lecture 4: Huffman Coding, Block Coding and Fundamental Limits of Compression
Lecture 5: Signals and Frequency Representation
Lecture 6: Fourier Series and Fourier Cosine Series I
Lecture 7: Fourier Series and Fourier Cosine Series II
Lecture 8: Fourier Transform and Discrete Fourier Transform
Lecture 9: Analog to Digital: the Sampling Theorem
Lecture 10: Digital to Analog: Interpolation and the Stroboscopic Effect
Lecture 11: Communication Channels and Systems
Lecture 12: Modulation and Bandwidth, On-Off Keying, Upconversion
Lecture 13: Error Correcting Codes Hamming codes, Hadamard codes
Lecture 14: Convolutional Codes
Lecture 15: Viterbi Decoding
Lecture 16: Exam
Lecture 17: “The Bit Player”
Lecture 18: Conditional Probability, Bit Error Rates
Lecture 19: Decision Making with noisy observations and Channel Capacity