SIMG-713
Noise and Random Processes

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Course Outline

Course Schedule

Homework

LECTURE NOTES
Lecture 1-Probability (Small) (Large)
Lecture 2-Random Variables (Small) (Large)

Lecture 3-Joint Probabilities (small) (Large)
Lecture 4-Functions of Random Variables (Small)(Large)
Lecture 5-Moments and Characteristic Functions (Small)(Large)
Lecture 6 - Repeated Trials and Law of Large Numbers (Small) (Large)
Lecture 7 - Poisson and Normal Distributions (Small)(Large)
Lecture 8-Photon Detection (Small) (Large)
Lecture 9 - Detective Quantum Efficiency (Small) (Large) (Corrected 4/16)
Lecture 10 -DQE of Image Intensifier (Small) (Large)
Lecture 11-Correlation in Random Processes (Small) (Large)

Lecture 12 - Introduction to Random Processes (Small) (Large)
Lecture 13 - Linear Filtering of Random Processes (Small) (Large)
Lecture 14 - Discrete Filter Representation of Random Processes (Small) (Large)
Lecture 15 - Power Spectrum Estimation (Small) (Large)

Lecture 16 - Handwritten notes distributed in class.
Lecture 17 - Random process generation and analysis (Small) (Large)

NOTES
Chapter 1-Probability
Chapter 2-Random Variables
Chapter 3-Averages
Chapter 4-Repeated Trials
Chapter 5-Photon Detection
Chapter 6-Detective Quantum Efficiency
Chapter 7-Random Process
Chapter 7-Digital Filter

Software
f1.pro f2.pro f3.pro
filter.pro
periodogram.pro
correlogram.pro

Midterm Exam Review Questions

Final Exam Review Outline and Questions

Paper on DQE in XRAY imaging system

DQE in Crystallography

Abstracts of papers by I A. Cunningham