# Oversampling

**oversampledoverachievingoversample**

In signal processing, oversampling is the process of sampling a signal at a sampling frequency significantly higher than the Nyquist rate.wikipedia

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### Sampling (signal processing)

**sampling ratesamplingsample rate**

In signal processing, oversampling is the process of sampling a signal at a sampling frequency significantly higher than the Nyquist rate.

Although the use of oversampling can completely eliminate aperture error and aliasing by shifting them out of the pass band, this technique cannot be practically used above a few GHz, and may be prohibitively expensive at much lower frequencies.

### Audio bit depth

**24-bitbit depthresolution**

Oversampling is capable of improving resolution, reducing noise and can be helpful in avoiding aliasing and phase distortion by relaxing anti-aliasing filter performance requirements.

However, techniques such as dithering, noise shaping and oversampling mitigate these effects without changing the bit depth.

### Anti-aliasing filter

**anti-aliasinganti-aliasing (AA) filteroptical low-pass filter**

Oversampling is capable of improving resolution, reducing noise and can be helpful in avoiding aliasing and phase distortion by relaxing anti-aliasing filter performance requirements.

For this reason, many practical systems sample higher than would be theoretically required by a perfect AAF in order to ensure that all frequencies of interest can be reconstructed, a practice called oversampling.

### Analog-to-digital converter

**ADCanalog to digital converteranalog-to-digital conversion**

In practice, oversampling is implemented in order to reduce cost and improve performance of an analog-to-digital converter (ADC) or digital-to-analog converter (DAC).

The resolution determines the magnitude of the quantization error and therefore determines the maximum possible average signal-to-noise ratio for an ideal ADC without the use of oversampling.

### Dither

**ditheringditheredAtkinson dithering**

Adding some dithering noise to the input signal can actually improve the final result because the dither noise allows oversampling to work to improve resolution.

Unfortunately, however, it still results in repeatable and determinable errors, and those errors still manifest themselves as distortion to the ear (though oversampling can reduce this).

### Oversampled binary image sensor

Oversampled binary image sensor

In this case, the corresponding pixel sizes (around 50~nm ) are far below the diffraction limit of light, and thus the image sensor is oversampling the optical resolution of the light field.

### Delta-sigma modulation

**delta-sigmadelta-sigma modulateddelta-sigma modulator**

Certain kinds of A/D converters known as delta-sigma converters produce disproportionately more quantization noise in the upper portion of their output spectrum.

This effect becomes more dramatic with increased oversampling, which allows for quantization noise to be somewhat programmable.

### Digital-to-analog converter

**DACDACsdigital to analog converter**

In practice, oversampling is implemented in order to reduce cost and improve performance of an analog-to-digital converter (ADC) or digital-to-analog converter (DAC).

Oversampling DACs or interpolating DACs such as those employing delta-sigma modulation, use a pulse density conversion technique with oversampling. Speeds of greater than 100 thousand samples per second (for example, 192 kHz) and resolutions of 24 bits are attainable with delta-sigma DACs.

### Upsampling

**higher sampling rateTime expansionup-sampling**

Here, samples are interpolated in the digital domain to add additional samples in between, thereby converting the data to a higher sample rate, which is a form of upsampling.

Oversampling

### Signal processing

**signal analysissignalsignal processor**

In signal processing, oversampling is the process of sampling a signal at a sampling frequency significantly higher than the Nyquist rate.

### Nyquist rate

**Nyquist limitNyquist sampling rateNyquist**

In signal processing, oversampling is the process of sampling a signal at a sampling frequency significantly higher than the Nyquist rate.

### Frequency domain

**frequency-domainfrequencyspectral analysis**

Theoretically, a bandwidth-limited signal can be perfectly reconstructed if sampled at the Nyquist rate or above it. The Nyquist rate is defined as twice the highest frequency component in the signal.

### Noise

**acoustic noisenoisynoise immunity**

Oversampling is capable of improving resolution, reducing noise and can be helpful in avoiding aliasing and phase distortion by relaxing anti-aliasing filter performance requirements.

### Aliasing

**aliasedaliastemporal aliasing**

### Phase distortion

### Nyquist frequency

**NyquistN/2 different frequenciesNyquist component**

Without oversampling, it is very difficult to implement filters with the sharp cutoff necessary to maximize use of the available bandwidth without exceeding the Nyquist limit.

### Digital filter

**filterdigitaldigital filters**

Once sampled, the signal can be digitally filtered and downsampled to the desired sampling frequency.

### Downsampling (signal processing)

**downsamplingdecimationdownsampled**

Once sampled, the signal can be digitally filtered and downsampled to the desired sampling frequency.

### Integrated circuit

**integrated circuitsmicrochipchip**

In modern integrated circuit technology, the digital filter associated with this downsampling are easier to implement than a comparable analog filter required by a non-oversampled system.

### Analogue filter

**analog filteranalogvoice frequency telegraphy**

In modern integrated circuit technology, the digital filter associated with this downsampling are easier to implement than a comparable analog filter required by a non-oversampled system.

### Dynamic range

**DRdynamicdynamic and tonal range**

When oversampling by a factor of N, the dynamic range also increases a factor of N because there are N times as many possible values for the sum.

### Signal-to-noise ratio

**signal to noise ratioSNRsignal-to-noise**

However, the signal-to-noise ratio (SNR) increases by \sqrt{N}, because summing up uncorrelated noise increases its amplitude by \sqrt{N}, while summing up a coherent signal increases its average by N. As a result, the SNR increases by \sqrt{N}.

### Signal

**signalselectrical signalelectrical signals**

This averaging is only effective if the signal contains sufficient uncorrelated noise to be recorded by the ADC.

### White noise

**whitestaticnoise**

This averaging is only effective if the signal contains sufficient uncorrelated noise to be recorded by the ADC.

### Uncorrelatedness (probability theory)

**uncorrelated**

If multiple samples are taken of the same quantity with uncorrelated noise added to each sample, then averaging N samples reduces the noise power by a factor of 1/N.