CALCULATORS / SIGNALS, SAMPLING AND DATA
Ideal ADC quantization-noise estimate calculator
Ideal uniform ADC quantization noise; full-scale uncorrelated error assumption.
SCENARIO COMPARISON
Compare the numbers.
This source describes an analytical model. Its quantities and checks are the view.
| Scenario | stepV | noiseRmsmV | idealSineSnrDb |
|---|---|---|---|
| 0.000805664 | 0.232575 | 74.0081 | |
| 0.000644531 | 0.18606 | 74.0081 |
All calculated quantities are listed with the inputs. Switch to Source to inspect the equations.
Change an input to see the consequences.
BASELINE INPUTS
CALCULATED
Edits change the baseline source.
Illustrative first-order example. Checks are editable requirements, not design standards. The broader topic may require additional equations, data, and validation.
Formula and units
This example uses the following equations. Input names and units match the editable source above.
- step
step = fullScale/2^bits [V]- noise rms
noiseRms = step/sqrt(12) [mV]- ideal sine snr db
idealSineSnrDb = 6.0206*bits+1.7609
Original worked example
These are the baseline values in the downloadable source. Edits above let you test your own values.
Given
- full scale
- 3.3 V
- bits
- 12
Calculated
- step
- 0.000805664 V
- noise rms
- 0.232575 mV
- ideal sine snr db
- 74.0081
Assumptions and limits
Ideal uniform ADC quantization noise; full-scale uncorrelated error assumption.
The requirement checks use the limits written in this example. Passing a check does not establish that the model covers every load, material behavior, or operating condition in a real design.
Download this .napkin example ↓Take it further with your agent
Napkin keeps the inputs, equations, checks and assumptions together in one study. Your agent sets it up; you change the numbers.
codex 'Use Napkin (https://napkin.engineering/mcp, or the local Napkin plugin) to build a study: Ideal ADC quantization-noise estimate. Inputs: bit depth; range; signal model; bandwidth. Outputs: conditional quantization-noise and ideal SNR. Model scope: Sampled-data models with stated bandwidth and noise assumptions. Read napkin_capabilities and the current snapshot. Ask me for the values that matter, label assumptions with units, author .napkin source, validate it and apply it with napkin_source using the current revision, then open the study. Add checks for the limits I supply. Keep unsupported analyses explicit.'Claude needs the Napkin connector; Codex needs the Napkin plugin. Set up your agent ↗
The broader study
The topic brief below describes the broader scope. The worked example above states the particular calculation it implements.
- Inputs: bit depth, range, signal model, bandwidth
- Outputs: conditional quantization-noise and ideal SNR
- Modes: calculate, compare, sweep
- Drawing: Signal, samples and spectrum
EXECUTABLE WORKED EXAMPLE · FIRST-ORDER MODEL · CHECK THE SCOPE & ASSUMPTIONS
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