PRECISION MEASUREMENTS
General concepts for predicting, characterizing, and reducing noise in measurements. Address the key questions of all experimentalists: (1) How can I improve my signal-to-noise ratio? (2) What is the ultimate detection limit of my measurement approach? Knowledge of Matlab programming and basic circuit design [such as E C E 230 ] is required.
Prerequisites & course information
Requisites: Graduate/professional standing Course Designation: Grad 50% - Counts toward 50% graduate coursework requirement Repeatable for Credit: No Last Taught: Fall 2026 Learning Outcomes: 1. Differentiate between different sources of measurement noise Audience: Graduate 2. Employ noise circuit analysis to predict the detection limit of a measurement Audience: Graduate 3. Characterize measurement noise in the frequency domain Audience: Graduate 4. Design and test analog filter circuits Audience: Graduate 5. Implement lock-in detection techniques to measure small signals Audience: Graduate Learning Outcomes: 1. Differentiate between different sources of measurement noise Audience: Graduate 2. Employ noise circuit analysis to predict the detection limit of a measurement Audience: Graduate 3. Characterize measurement noise in the frequency domain Audience: Graduate 4. Design and test analog filter circuits Audience: Graduate 5. Implement lock-in detection techniques to measure small signals Audience: Graduate
Sources
- Course catalogue ↗2026-2027