**fs = 1/T**. Its units are samples per second or hertz e.g. 48 kHz is 48,000 samples per second.

How do you calculate sampling time?

**sampling time formula**.

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The sampling frequency should be **at least double the maximum frequency**. If your measurement is done in the pass-band (2.38 GHz-2.46 GHz), so the maximum frequency is 2.46 GHz which means that the sampling frequency should be at least 2×2. 46 GHz = 4.92 GHz.

Sampling rate (sometimes called sampling frequency or Fs) is **the number of data points acquired per second**. A sampling rate of 2000 samples/second means that 2000 discrete data points are acquired every second. … The inverse of sampling frequency (Fs) is the sampling interval or Δt.

MINIMUM NUMBER OF SAMPLES The sampling theorem states that a real signal, f(t), which is band-limited to f Hz can be reconstructed without error from samples taken uniformly at a rate R > 2f samples per second. This minimum sampling frequency, **fs = 2f Hz**, is called the Nyquist rate or the Nyquist frequency (6).

The sampling period is **the time difference between two consecutive samples in a Sound**. It is the inverse of the sampling frequency. For example: if the sampling frequency is 44100 Hz, the sampling period is 1/44100 = 2.2675736961451248e-05 seconds: the samples are spaced approximately 23 microseconds apart.

The sampling frequency determines **the distance between the midpoint of one pixel to the midpoint of an adjacent pixel**.

The **frequency fn = 1/2Δt** is called the Nyquist frequency. When spectra are presented for digital data, the highest frequency shown is the Nyquist frequency. For IRIS broadband seismic stations, Δt = 0.05 s, so the Nyquist frequency is 10 Hz.

The higher the sampling frequency, the easier it is **for a low-pass filter to extract the original signal with no (significant) loss of information**, because the filter transition band falls between the copies of the signal spectrum.

For example, suppose that fs = 65 Hz, fN = 62.5 Hz, which corresponds to 8-ms sampling rate. The alias frequency then is **fa = |2 × 62.5 − 65|** = 60 Hz.

In fact, the maximum bandwidth of a sampled waveform is determined exactly by its sampling rate; the maximum frequency representable in a sampled waveform is termed its Nyquist frequency, and is **equal to one half the sampling rate**.

The sampling rate or sampling frequency fs of the measuring system (e.g. 48 kHz). This is the **average number of samples obtained in one second** (samples per second). The selected number of samples; the blocklength BL. This is always an integer power to the base 2 in the FFT (e.g., 2^10 = 1024 samples)

The sampling interval is an important parameter which must be chosen carefully, if **measurements of the direct, global, and diffuse irradiance** or illuminance are carried out to determine their averages over a given period.

The spatial resolution of a digital image is determined by **the distance between pixels**, known as the sampling interval, and the accuracy of the digitizing device. The numerical value of each pixel in the digital image represents the intensity of the optical image averaged over the sampling interval.

The **size of the matrix determines the size of the pixels**. For example, if you have a 10 × 12 and a 14 × 17 computed radiography (CR) cassette and both have a 512 × 512 matrix, then the 10 × 12 cassette will have smaller pixels.

They include **direct solid-state** (Figure 3) and indirect photo-stimulable phosphor plates (PSP) that are similar to flexible radiographic film (Figure 4). The solid-state technology uses different semi-conductor-based detectors 1) CCD, 2) CMOS, and 3) flat panel. Figure 3.

Nyquist frequency. The Nyquist frequency is the bandwidth of a sampled signal, and is **equal to half the sampling frequency of that signal**.

The Nyquist rate is the minimal frequency at which you can sample a signal without any undersampling. It’s double the highest frequency in your continous-time signal. Whereas the **Nyquist frequency is half of the sampling rate**.

According to the Shannon Sampling Theorem, **use a sampling frequency at least twice the maximum frequency component in the sampled signal** to avoid aliasing.

As the sampling frequency decreases, the signal separation also decreases. When the sampling frequency drops below the Nyquist rate, **the frequencies will crossover and cause aliasing**.

Use **44,100 Hz (44.1 kHz)** = CD-quality sample rate for professional audio work Each sample has 16 bits of information.

You will need to know the standard deviation of the population in order to calculate the sampling distribution. Add all of the observations together and then **divide by the total number of observations in the sample**.

If a random sample of n observations is taken from a binomial population with parameter p, the sampling distribution (i.e. all possible samples taken from the population) will have a standard deviation of: Standard deviation of binomial distribution = **σp = √[pq/n]** where q=1-p.

(Also called Nyquist frequency.) The highest frequency that can be measured using discretely sampled data. It is given by **nf (rad s-1) = π/Δt**, where nf is the Nyquist frequency and t is the time increment between observations.

As you already know, sampling of a **continuous-time signal results in repeating its spectrum in the frequency domain**. … When the sampling rate is not large enough (not larger than 2B Hz), then interference among adjacent bands will occur, and this results in the phenomenon of aliasing.

Undersampling. In signal processing, undersampling or bandpass sampling is a **technique where one samples a bandpass-filtered signal at a sample rate below its Nyquist rate**, but is still able to reconstruct the signal.

Sampling rate or sampling frequency defines **the number of samples per second (or per other unit) taken from a continuous signal** to make a discrete or digital signal.

- Replace all coefficients of the FFT with their square value (real^2+imag^2). …
- Take the iFFT.
- Find the largest peak in the iFFT.

DFTFFTThe DFT has less speed than the FFT.It is the faster version of DFT.

When doing digital filter design you normally work with normalised frequency, which is **just the actual frequency divided by the sample rate**. So in your example where you want to specify a cut-off of 50 Hz at a sample rate of 500 Hz then you would specify this as a normalised frequency of 0.1.

Say you have X beats (quarter notes) per **minute** (BPM) = 60 seconds. Then one beat takes up 60/X seconds. If you record with a 44.1k sample rate, you have 44100 samples per second. And so one quarter = 60/X seconds = 60/X * 44100 samples.

Discrete-time frequencies Suppose this represents an audio signal that is sampled at 8000 samples/second. Then to convert f to Hertz, just watch the units: **f [cycles/sample] × 8000 [samples/second] = 8000f [cycles/second]**.

**The more samples that are taken, the more detail about where the waves rise and fall is recorded and the higher the quality of the audio**. Also, the shape of the sound wave is captured more accurately. … The unit for the sample rate is hertz (Hz) . 44,100 samples per second is 44,100 hertz or 44.1 kilohertz (kHz).

The size of the area viewed is determined **by multiplying the IFOV by the distance from the ground to the sensor (C)**. This area on the ground is called the resolution cell and determines a sensor’s maximum spatial resolution.

When describing digital images, gray-level resolution is a term that refers **to the number of shades of gray utilized in preparing the image for display**. … The number of bits utilized in the displayed image is presented directly above the slider, as is the total number of gray levels.

Term: Sampling rate (image) Definition: **The spatial frequency of the digital sampling**. The reciprocal of the center-to-center distance between adjacent pixels.