Filters and Signals
Model class: Exact ideal relationship
Coherent sampling planner
Find the coherent test-tone frequency for a chosen FFT bin, sample rate, and record length, and check the coprime condition.
Interactive engine
Start with the stated conditions.
Values stay in this browser. Choose a representative scenario, then calculate deliberately.
Example ready
Calculate to inspect the result.
The result will identify the direct answer, assumptions, and any warning that changes the next decision.
How much does each input matter?
Each row holds every other input fixed at its current value and moves one input by ±10%, using the same model as the main result. It identifies which input is the binding lever, not a full tolerance stack.
Assumptions to check
- The entered coherent-sampling values represent the stated operating condition.
- This exact ideal relationship is evaluated in the declared lumped or first-pass model.
- A coherent-sampling calculation is not a component qualification or safety approval.
What this coherent-sampling calculation establishes
Find the coherent test-tone frequency for a chosen FFT bin, sample rate, and record length, and check the coprime condition. The useful result is the stated electrical quantity and the decision it supports, not an unstated claim about a finished product. This engine keeps the governing relationship visible so an input, unit, condition, or model boundary can be reviewed before a value becomes a component or layout choice.
Coherent sampling requires the input frequency to equal bin number times sample rate divided by record length, with the bin coprime to the record length. Treat the number as a first-pass result for the declared operating point. When a source, load, temperature, frequency, waveform, component tolerance, or measurement condition changes, repeat the calculation at the relevant corner rather than assuming the nominal answer persists.
Worked decision context
fs = 1 MHz, N = 1000, and bin k = 123 give a coherent test tone of 123 kHz; gcd(123, 1000) = 1. That example verifies the equation and illustrates the scale of the result, but it does not select a part by itself. Compare the result with available values, ratings, tolerance bands, and the receiving circuit or physical environment before implementation.
Use the primary output to identify the binding constraint. If it leaves little margin, document which input dominates and use selected-part data, a higher-fidelity model, simulation, or measurement. This is especially important when a small numerical difference changes a thermal, timing, noise, or reliability decision.
Limits and validation handoff
It checks one candidate bin. When the bin is not coprime to the record length, a nearby integer search is needed to find a valid coherent frequency. The calculation does not silently include omitted parasitics, installation conditions, manufacturing variation, or product policy. Those conditions can be decisive even when the arithmetic is exact for the selected model.
Record inputs, units, model assumptions, and the intended decision with the result. Verify the leading risk against the selected component data sheet and a representative measurement when the circuit has consequential energy, high voltage, safety, compliance, or reliability requirements.
Common mistakes
- Treating the coherent-sampling result as a guaranteed operating limit rather than a first-pass exact ideal relationship estimate.
- Mixing a data-sheet value measured under one condition with this coherent-sampling calculation performed at another.
- Selecting a component before checking the boundary this calculation names: it checks one candidate bin. When the bin is not coprime to the record length, a nearby integer search is needed to find a valid coherent frequency.
Model limit and handoff
Keep the entered coherent-sampling conditions with the calculation, then validate the binding limit using the selected component, physical implementation, and representative operating corner.
FAQs
Is this coherent-sampling result sufficient to approve a design?
No. It applies exact ideal relationship reasoning to the entered coherent-sampling values and names the checks that still need selected-part data, a higher-fidelity model, or measurement. It checks one candidate bin. When the bin is not coprime to the record length, a nearby integer search is needed to find a valid coherent frequency.
What does this coherent-sampling calculator assume that could make the result wrong?
Coherent sampling requires the input frequency to equal bin number times sample rate divided by record length, with the bin coprime to the record length. If the entered values do not match the real operating condition, the result no longer describes the actual circuit.
Where should this coherent-sampling result go next?
Compare this coherent-sampling result with Sampling, aliasing, windows, and FFT records, then use the stated next decision below the calculator to move from this first-pass number toward an implementation.