Catalog Description: This course covers the fundamentals of probability and random processes useful in fields such as networks, communication, signal processing, and control. Sample space, events, probability law. Conditional probability. Independence. Random variables. Distribution, density functions. Random vectors. Law of large numbers. Central limit theorem. Estimation and detection. Markov chains.

Units: 4

Related Areas:

• Information, Data, Network, and Communication Sciences (IDNCS)
• Signal Processing (SP)

Prerequisites: EECS 16A and EECS 16B.

Formats:
Fall: 3 hours of lecture and 1 hour of discussion per week
Spring: 3 hours of lecture and 1 hour of discussion per week

Grading Basis: letter

Final Exam Status: Written final exam conducted during the scheduled final exam period

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• EE enrollment policies
• HKN course maps