18-752: Estimation, Detection, and Identification

Course Description

Decision theory: Binary hypothesis testing, M-ary testing, Bayes, Neyman-Pearson, Min-Max. Performance. Probability of error, ROC.
Estimation theory: linear and nonlinear estimation, parameter estimation. Bayes, MAP, maximum likelihood, Cramér-Rao bounds. Bias, efficiency, consistency. Asymptotic properties of estimators. Orthogonal decomposition of random processes and harmonic representation. Waveform detection and estimation. Wiener filtering and Kalman-Bucy filtering.
Elements of identification: Recursive algorithms, spectral estimation.

  • Number of Units: 12

  • Pre-requisite: 18-751 and senior or graduate standing

  • Course Area: Signals and Systems, Signal Processing and Communications

  • Tentative Syllabus: Given here

Instructor and Administrative Staff

  • Instructor: Prof. Osman Yağan                              diamond Teaching Assistant: Serim Park

  • Office Location: Bldg. 23, 121B                             diamond Office: HH c120

  • Email Address: oyagan@ece.cmu.edu                 diamond Email: serimp@ece.cmu.edu

  • Office Hours: Thursday, 3:30pm-4:30pm          diamond Office Hours: Wednesday, 4pm-6pm

Class Schedule

  • Lecture: Tuesdays and Thursdays 4:30 pm – 6:20 pm (EST), 1:30 pm - 3:20 pm (PST)

  • Location: Pittsburgh: WEH 5328      Silicon Valley: Bldg. 23, Room 211

Textbooks

  • Louis L. Scharf, Probability, Statistical Signal Processing, Detection, Estimation, and Time Series Analysis, Addison-Wesley, 1991.

  • Harry Van Trees, Kristine L. Bell, Detection, Estimation, and Modulation Theory Part I, Second Edition, Wiley, 2013 (Recommended).

Grading

Homeworks 25%
Project 25%
Tests (2 tests, 25% each) 50%