Overview
Week 5 at a Glance
Butterworth filter designSallen-Key topologyNyquist-Shannon theoremAnti-aliasing filterADC quantization errorDAQ system specification
Why it matters in practice. Aliasing is catastrophic and irreversible — once a signal is sampled below the Nyquist rate, the false frequency content cannot be removed. Every DAQ system you design or use for the rest of your career must address this.
Objectives
What You Will Be Able to Do
Course objectives (CO) define program-level skills. Module objectives (MO) define specific weekly targets that build toward them.
Course Objectives (CO)
CO3: Design signal conditioning circuits (active filters) to meet target specifications.
CO4: Configure a data acquisition system correctly; apply Nyquist criterion; diagnose and prevent aliasing.
Module Objectives (MO) — Week 5
Design a first- or second-order Butterworth low-pass filter using the Sallen-Key topology for a specified cutoff frequency.
CO3
CO3
Apply the Nyquist-Shannon sampling theorem to specify the minimum sampling rate for a given signal bandwidth.
CO4
CO4
Calculate ADC resolution, quantization noise, and ideal SNR for a given bit depth and reference voltage.
CO4
CO4
Specify an anti-aliasing filter cutoff frequency and order given sampling rate and required stop-band attenuation.
CO3
CO3
Select ADC type (SAR, delta-sigma, flash) appropriate for a given combination of speed and resolution requirements.
CO4
CO4
Review these objectives before you start each assignment. They map directly to what is assessed on the quiz, homework, and exams.
Suggested Learning Path
How to Work Through This Week
Follow this sequence. Each step prepares you for the next. Do not attempt graded work before completing the instructional material it depends on.
1
Read Alciatore Ch. 6 (assigned sections)
Focus on the Nyquist theorem derivation, the anti-aliasing filter requirement, and the Sallen-Key design equations. Work through the filter component calculation example by hand.
2
Attend Lecture
Lecture 1 covers active filter design (Butterworth, Sallen-Key, cutoff frequency). Lecture 2 covers DAQ architecture (S/H, MUX, ADC types, quantization error, ENOB). Both lectures include problem sessions.
3
Lab: DAQ System Characterization
Configure your Arduino ADC, measure quantization noise experimentally, and verify the Nyquist criterion by sampling a known-frequency sine wave at multiple rates. Observe aliasing intentionally at sub-Nyquist rates.
4
Begin Module 3 Homework
Module 3 Homework (Weeks 5-6 content) is due end of Week 6. The filter design problems map directly to this week's Lecture 1 content.
Instructional Material
Required Readings, Videos, and Resources
Complete all required items before moving to graded activities. The Aligns to column maps each resource to the module objectives it directly supports.
| Resource | What You Will Gain | Aligns to | Est. Time |
|---|---|---|---|
| Read Alciatore Ch. 6 — Signal Conditioning and Data Acquisition (5th Ed.) |
Sallen-Key design equations, Butterworth vs. Chebyshev trade-offs, Nyquist theorem, anti-aliasing requirements, ADC architecture, quantization error, and ENOB. | MO1-MO5 | 75 min |
| Watch Micro-lecture: Aliasing Demonstration |
4-minute video showing aliasing in time-domain signals and frequency-domain spectra. Seeing aliasing is the fastest way to understand why anti-aliasing filters are non-negotiable. | MO2, MO4 | 4 min |
| Lab Lab: DAQ System Characterization with Arduino |
Measure quantization noise, observe aliasing, and verify Nyquist criterion experimentally on your own Arduino hardware. | MO2, MO3 | ~2 hr lab |
Graded Learning Activities
Assignments and Due Dates
All graded work is submitted through Canvas. Complete the listed prerequisites before attempting each assignment.
| Assignment | Prerequisites | What Is Assessed | Aligns to | Points |
|---|---|---|---|---|
| Module 3 Homework: Filters, DAQ, and FFT End of Week 6 |
Complete both Ch. 6 and Ch. 7 (Week 6) readings before attempting all problems. Filter design problems use Week 5 content; FFT problems use Week 6 content. | Sallen-Key filter design, anti-aliasing specification, ADC quantization calculation, and FFT analysis of lab-measured waveforms. | MO1-MO5 | 50 pts |
Academic integrity. The aliasing observation in this week's lab requires you to run the experiment on your own Arduino at the specified sampling rates. The waveform data in your report must match your actual recorded output.