Conversion & CalculationLive🔒 Private

Nyquist Frequency Calculator

Calculate Nyquist frequency and minimum sampling rate. Free online Nyquist calculator. No signup, 100% private, browser-based.

Nyquist Frequency Calculator

Frequency (Hz)

22050

How it works

The Nyquist frequency is half the sampling rate: f_Nyquist = f_sample / 2. It represents the highest frequency that can be unambiguously represented in a digital signal without aliasing. Any signal component above the Nyquist frequency aliases to a lower frequency.

**Aliasing explained** Aliasing occurs when an analog signal contains frequencies above the Nyquist limit. These high-frequency components are indistinguishable from lower-frequency components after sampling. A 9 kHz signal sampled at 10 kHz (Nyquist = 5 kHz) aliases to 1 kHz (|9 - 10| = 1 kHz). The alias appears as a spurious signal that cannot be separated from the real signal.

**Baseband vs. bandpass sampling** Baseband sampling: the standard case — signal from DC to f_max requires f_s > 2 × f_max. Bandpass (undersampling): if a signal occupies a narrow band centered at a high frequency, it can be sampled at a lower rate (f_s > 2 × bandwidth) and the signal aliases to baseband. This is intentional aliasing used in software-defined radio to downconvert signals without a hardware mixer.

**Nyquist in control systems** The Nyquist stability criterion analyzes open-loop frequency response to determine closed-loop stability. Separately, control systems are sampled systems — the sampling rate must be much higher than the process bandwidth (typically 10–20× the bandwidth, not just 2×) to avoid stability problems from sampling delay.

**Two-sided spectrum and negative frequencies** The full spectrum from -f_s/2 to +f_s/2 has total width f_s. Negative frequencies are mathematical artifacts of complex exponential representation; for real signals, the spectrum is symmetric about zero. The Nyquist interval is therefore f_s in bandwidth, but usable for real signals only from 0 to f_Nyquist.

Frequently Asked Questions

How do I choose a sampling rate for a vibration monitoring system?
Sample rate must be at least 2× the highest frequency of interest. For machine vibration monitoring: rolling element bearing defect frequencies (BPFI, BPFO) are typically 3–10× shaft frequency. At 3600 RPM (60 Hz), bearing frequencies may reach 600 Hz. To capture harmonics up to 10th: 6,000 Hz × 2 = 12 kHz sample rate minimum. For rotating machinery: common practice is sample at 2.56× the maximum analysis frequency (analysis frequency = Nyquist × 0.8 to allow for anti-aliasing filter roll-off). At 12 kHz sample rate: f_Nyquist = 6 kHz, maximum reliable analysis frequency ≈ 4,800 Hz.
What causes aliasing in practice and how do I avoid it?
Aliasing sources: insufficient anti-aliasing filter before ADC (most common), non-bandlimited signal source, undersampled CCD or CMOS sensors in cameras (moiré patterns on fine textures), and intentional undersampling without proper filtering. Prevention: always implement a hardware anti-aliasing filter with cutoff at least at f_Nyquist, with sufficient rolloff by f_Nyquist. Practical filter order: for a 5× oversampled ADC (anti-aliasing at 5× Nyquist), a 4th-order filter achieves >80 dB attenuation at the image frequency. Digital cameras use optical low-pass filters (birefringent crystal) before the sensor to prevent spatial aliasing.
What is the Nyquist stability criterion in control systems?
The Nyquist stability criterion (different from sampling Nyquist) analyzes stability of a closed-loop feedback system by examining the open-loop frequency response. Plot the open-loop transfer function G(jω)H(jω) on a complex plane for ω from -∞ to +∞. Count encirclements of the -1+j0 point. Stability criterion: N = Z - P, where N is clockwise encirclements, Z is closed-loop RHP (unstable) poles, P is open-loop RHP poles. If P = 0, no encirclements of -1 → stable. Gain margin (how much gain can increase before instability) and phase margin (how much phase lag before instability) are read from the Nyquist plot.
How is the Nyquist-Shannon theorem applied in digital communications?
Shannon's capacity theorem extends Nyquist: C = B × log₂(1 + SNR), where C is channel capacity (bits/s), B is bandwidth (Hz), and SNR is signal-to-noise ratio. For a 20 MHz Wi-Fi channel at SNR = 30 dB (1000:1): C = 20×10⁶ × log₂(1001) ≈ 200 Mbps theoretical maximum. Practical Wi-Fi achieves 60–80% of this. Nyquist's theorem says maximum symbol rate = 2B symbols/second (Nyquist rate). With 1024-QAM (10 bits/symbol): data rate = 2 × 20 MHz × 10 bits = 400 Mbps/spatial stream. MIMO adds multiple streams: Wi-Fi 6 with 8×8 MIMO achieves up to 9.6 Gbps theoretical maximum.