CSC310H1: Information Theory

Hours

24L/12T

Measuring information. Entropy, mutual information and their meaning. Probabilistic source models and the source coding theorem. Data compression. Noisy channels and the channel coding theorem. Error correcting codes and their decoding. Applications to inference, learning, data structures and communication complexity.

Prerequisite

60% or higher in CSC148H1/ 60% or higher in CSC148H5/ 60% or higher in CSCA48H3/ 60% or higher in CSC111H1; CSC263H1/ CSC263H5/ CSCB63H3/ CSC265H1; MAT223H1/ MAT240H1 Prerequisite for Faculty of Applied Science and Engineering students: ESC190H1; ECE345H1/ ECE358H1/ MIE245H1; MAT185H1/ MAT188H1

Exclusion

NOTE: Students not enrolled in the Computer Science Major or Specialist program at A&S, UTM, or UTSC, or the Data Science Specialist at A&S, are limited to a maximum of 1.5 credits in 300-/400-level CSC/ECE courses.

Breadth Requirements

The Physical and Mathematical Universes (5)

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CSC310H1: Information Theory