ECE 645: Estimation Theory
Professor Stanley H. Chan, Purdue University, Spring 2015
Announcements
- 03/23/2015 Schedule of Lecture Notes updated.
- 01/16/2015 Schedule of Lecture Notes updated.
- 12/11/2014 Welcome to ECE 645! This is the official course website.
Course Information
- Lecture: MWF 16:30 - 17:20
- Room: EE 226
- Instructor: Professor Stanley H. Chan
- Room: MSEE 218
- Email: stanleychan@purdue.edu
- Office Hour: Tuesday 4pm - 5pm, or by email appointment.
- Syllabus: Download Syllabus PDF (Tentative) (Last updated: 1/12/2015)
Student Lecture Notes
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Guideline PDF | Schedule PDF | LaTeX Template ZIP | LaTeX Template PDF
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Student Lecture Note 01: Bayes Decision Theory (Lecture 1-4, by S. Chatzidakis)
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Student Lecture Note 02: Neyman Pearson Test (Lecture 5-7, by J. Jeong)
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Student Lecture Note 03: Composite Hypothesis Testing (Lecture 8-10, by H. Wen)
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Student Lecture Note 04: Limit Theory (Lecture 11-12, by J. Li)
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Student Lecture Note 05: Large Deviation Theory (Lecture 13-14, by S. Pereira)
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Student Lecture Note 06: Minimum Variance Unbiased Estimator (Lecture 15-17, by B. Vondersaar)
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Student Lecture Note 07: Maximum Likelihood Estimation (Lecture 18-20, by S. Fang)
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Student Lecture Note 08: Properties of MLE (Lecture 21-23, by H. Wen)
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Student Lecture Note 09: Bayesian Estimation (Lecture 24-27, by J. Jeong)
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Student Lecture Note 10: EM Algorithm (Lecture 28-31, by S. Fang)
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Student Lecture Note 11: Iterative Algorithm (Lecture 32-33, by B. Vondersaar)
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Student Lecture Note 12: Kalman Filter (Lecture 34-36, by S. Chatzidakis)
Hand Written Notes
- Lecture 01: 2015-01-14 Review of Probability
- Lecture 02: 2015-01-16 Bayes Decision Theory
- Lecture 03: 2015-01-21 Binary Hypothesis Testing
- Lecture 04: 2015-01-23 M-ary Hypothesis Testing
- Lecture 05: 2015-01-26 Trade off in False Alarm and Miss
- Lecture 06: 2015-01-28 Neyman Pearson Testing I
- Lecture 07: 2015-01-30 & 02-02 Neyman Pearson Testing II
- Lecture 08: 2015-02-04 Composite Hypothesis Testing I - Nuisance Parameter
- Lecture 09: 2015-02-06 Composite Hypothesis Testing II - Uniformly Most Powerful Test
- Lecture 10: 2015-02-09 Composite Hypothesis Testing III - LMP and GLRT
- Lecture 11: 2015-02-11 Law of Large Numbers
- Lecture 12: 2015-02-13 Central Limit Theorem
- Lecture 13: 2015-02-16 Large Deviation Analysis I Additional Reading
- Lecture 14a & Lecture 14b: 2015-02-18 & 02-20 Large Deviation Analysis II & III
- Lecture 14 Supp: Supplementary Note for Large Deviation III
- Lecture 15: 2015-02-23 MVUE I - Sufficient Statistics
- Lecture 16: 2015-02-25 MVUE II - Rao-Blackwell
- Lecture 17: 2015-02-27 MVUE III - Complete Family | Lecture 17 Supp
- Lecture 18: 2015-03-02 Maximum Likelihood I
- Lecture 19: 2015-03-04 Maximum Likelihood II (Fisher Information)
- Lecture 20: 2015-03-06 Maximum Likelihood III (Cramer-Rao Lower Bound)
- Lecture 21 & Lecture 22: 2015-03-09 & 03-11 Efficiency of MLE
- Mid Term Exam: 2015-03-13 | Solution PDF
- Lecture 23: 2015-03-23 Consistency of MLE
- Lecture 24: 2015-03-25 Bayesian Estimation I (MMSE, MMAE)
- Lecture 25: 2015-03-27 Bayesian Estimation II (MAP)
- Lecture 26: 2015-03-30 Bayesian Estimation III (Vector and Joint Gaussian)
- Lecture 27: 2015-04-01 Bayesian Estimation IV (LMMSE) | Lecture 27 Supp
- Lecture 28: 2015-04-03 EM Algorithm I (Basic Concepts) Additional Reading
- Lecture 29: 2015-04-06 EM Algorithm II (Gaussian Mixtures)
- Lecture 30: 2015-04-08 EM Algorithm III (Bernoulli Mixtures)
- Lecture 31: 2015-04-10 EM Algorithm IV (Convergence and Prior)
- Lecture 32: 2015-04-13 Iterative Algorithm for MLE and MAP MATLAB Code
- Lecture 33: 2015-04-15 Stein Unbiased Risk Estimator Reading 1 | Reading 2
- Lecture 34: 2015-04-17 Kalman-Bucy Filtering I
- Lecture 35: 2015-04-20 Kalman-Bucy Filtering II
- Lecture 36: 2015-04-22 Orthogonality Principles and Wiener-Hopf Equation
Homework
- Homework 01: Binary hypothesis testing, False alarm and Miss.
- Homework 02: M-ary hypothesis testing, Neyman-Pearson testing.
- Homework 03: UMP.
- Homework 04: LMP, GLRT.
- Homework 05: Large deviation.
- Homework 06: MVUE, MLE.
Projects
- Guideline PDF
- LaTeX Proposal Template ZIP | LaTeX Proposal Template PDF
- LaTeX Report Template ZIP | LaTeX Report Template PDF