liminfoADC/DAC Calculator
Free web tool: ADC/DAC Calculator
Ideal SNR
74.00 dB
6.02N + 1.76
ENOB
12.00 bits
LSB Size
805.664 µV
Quantization Levels
4,096
Q Noise (RMS)
232.575 µV
Q Noise (dBFS)
-77.02 dBFS
Nyquist Frequency
500.000 kHz
Noise Density
328.91 nV/\u221aHz
About ADC/DAC Calculator
The ADC/DAC SNR & ENOB Calculator is a free, browser-based tool for electronics engineers and signal processing professionals who need to characterize analog-to-digital or digital-to-analog converter performance. Enter the converter resolution in bits, full-scale range in volts, and sampling rate in kSPS/MSPS/GSPS to instantly compute key performance metrics. Ideal SNR is derived from the fundamental formula SNR = 6.02N + 1.76 dB, where N is the number of bits. This represents the theoretical maximum SNR for a perfect converter with only quantization noise.
The tool also calculates LSB size (Vfs / 2^N), quantization noise in RMS voltage and dBFS, Nyquist frequency (fs/2), and input-referred noise density in nV/√Hz. For real-world characterization, you can enter an optional measured SINAD value to compute ENOB (Effective Number of Bits) using the formula ENOB = (SINAD − 1.76) / 6.02. This lets you compare the theoretical ideal performance against what your actual hardware achieves, accounting for harmonics, jitter, and analog nonlinearities.
In DAC mode, the tool additionally shows the output voltage step size between adjacent codes (Vfs / (2^N − 1)) and the update period (1/fs), which are critical for audio DAC design, waveform generators, and control loop outputs. All calculations run client-side in your browser with no data transmitted to any server.
Key Features
- Calculates ideal SNR using the standard formula 6.02N + 1.76 dB for any bit resolution
- Computes ENOB from measured SINAD input using ENOB = (SINAD − 1.76) / 6.02
- Shows LSB size in mV or µV, quantization noise RMS, and quantization noise in dBFS
- Displays Nyquist frequency and input-referred noise density in nV/√Hz
- DAC mode: additional step voltage and update period output
- Sampling rate unit selection — kSPS, MSPS, or GSPS
- Optional SINAD input for real device ENOB calculation alongside ideal values
- 100% client-side processing — converter specifications never leave your browser
Frequently Asked Questions
What is the ideal SNR formula for an ADC?
The ideal SNR (Signal-to-Noise Ratio) for a perfect ADC with N bits is: SNR = 6.02 × N + 1.76 dB. This assumes the only noise source is uniform quantization noise, and the input signal is a full-scale sine wave. Each additional bit of resolution improves SNR by approximately 6 dB.
What is ENOB and how is it calculated?
ENOB (Effective Number of Bits) measures the actual resolution of a real converter accounting for all noise and distortion, not just quantization. It is calculated from SINAD (Signal-to-Noise and Distortion ratio) as: ENOB = (SINAD − 1.76) / 6.02. An ENOB lower than the nominal bit count indicates that harmonic distortion, clock jitter, or thermal noise degrades performance below the theoretical limit.
What is the difference between SNR and SINAD?
SNR measures the ratio of signal power to noise power, typically excluding harmonics. SINAD (Signal to Noise And Distortion) includes both noise and harmonic distortion components in the denominator. SINAD is therefore always equal to or worse than SNR. For a perfect ADC, SNR and SINAD are equal; real devices show a gap due to nonlinearity-induced harmonics.
What is quantization noise and how large is it?
Quantization noise arises because an ADC rounds the input to the nearest discrete level. For a uniform quantizer, the quantization noise RMS is LSB / √12. In dBFS, this equals −(6.02N + 1.76) dB for a full-scale sine wave input, which is just the negative of the ideal SNR. Reducing quantization noise requires increasing the bit resolution or applying dithering.
Why does Nyquist frequency matter for ADC selection?
By Nyquist-Shannon sampling theorem, an ADC can correctly represent signals up to half its sampling rate (the Nyquist frequency). Input signals above this frequency alias back into the baseband and appear as false frequency components. An anti-aliasing filter must be placed before the ADC to attenuate signals above the Nyquist frequency before sampling.
How does noise density help in system design?
Input-referred noise density (nV/√Hz) describes the ADC noise floor normalized to bandwidth. It allows engineers to calculate the total integrated noise over a specific signal bandwidth: total noise = noise density × √(bandwidth). This is useful for comparing ADCs with different sampling rates on a fair basis and for budgeting noise in a signal chain.
What is DAC step size and why does it matter?
DAC step size (also called LSB voltage) is the smallest output voltage change the DAC can produce: Vfs / (2^N − 1). It determines the minimum control resolution. For audio DACs, smaller step size means finer volume control. For control loops, it sets the minimum actuator command increment. Step size also relates to static linearity specs like INL and DNL.
What is a typical ENOB loss for a high-speed ADC?
High-speed ADCs (>100 MSPS) typically lose 0.5 to 2 bits of ENOB compared to their nominal resolution, primarily due to input-referred jitter and aperture uncertainty. A 12-bit ADC running at 1 GSPS might achieve only 9-10 ENOB in practice. This is why full ADC datasheets always specify ENOB and SINAD in addition to nominal bit count.