Signal-to-Noise Ratio (SNR) Calculator
Work out signal-to-noise ratio in decibels from two levels, from a voltage/amplitude or power ratio, or convert between SNR and the effective number of bits (ENOB).
SNR is how far your wanted signal sits above the noise — higher is cleaner. These are standard formulas; it’s a calculator, not a measurement.
SNR from two levels
SNR (dB) = signal level − noise level. Use any consistent dB scale (e.g. both in dBFS).
SNR from amplitude or power
Amplitude (voltage): SNR = 20·log₁₀(signal/noise). Power: SNR = 10·log₁₀(signal/noise). Pick which your numbers are.
SNR ↔ effective number of bits
For an ideal converter: SNR = 6.02·N + 1.76 dB, so ENOB = (SNR − 1.76) / 6.02. Edit either field.
Ideal SNR by bit depth
Theoretical best SNR of a perfect N-bit converter (6.02·N + 1.76 dB).
How SNR Works
Signal-to-noise ratio compares the level of the signal you want to the background noise you don’t, expressed in decibels. This SNR calculator works from three starting points: from two measured levels (simply the difference), from a voltage ratio using 20·log₁₀(signal/noise), or from a power ratio using 10·log₁₀(signal/noise) — the factor of two difference exists because power goes as amplitude squared. For example, a signal at −12 dBFS over a −72 dBFS noise floor gives 60 dB SNR. You can use the noise floor analyzer to measure an actual noise floor before plugging the value in here.
For digital systems, bit depth SNR follows the formula 6.02·N + 1.76 dB for N bits — about 98 dB for 16-bit and 146 dB for 24-bit. The effective number of bits (ENOB) works backwards from a measured SNR (or SINAD — signal-to-noise-and-distortion ratio) to say how many real bits of resolution you’re getting once thermal noise, quantization error, and harmonic distortion are all included. ENOB is always lower than the converter’s nominal bit depth because real-world ADCs are not ideal. SNR relates to, but is not the same as, dynamic range: dynamic range covers the span from the noise floor to the maximum undistorted signal, while SNR measures a specific signal against its noise floor. For a pure sinewave, SNR and dynamic range converge; for complex program material, they diverge.