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signal-to-noise ratio
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signal-to-noise ratio
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{{about|signals|statistics|Effect size|other uses|Signal to Noise (disambiguation)}}Signal-to-noise ratio (abbreviated SNR or S/N) is a measure used in science and engineering that compares the level of a desired signal to the level of background noise. SNR is defined as the ratio of signal power to the noise power, often expressed in decibels. A ratio higher than 1:1 (greater than 0 dB) indicates more signal than noise.While SNR is commonly quoted for electrical signals, it can be applied to any form of signal, for example isotope levels in an ice core, biochemical signaling between cells, or financial trading signals. Signal-to-noise ratio is sometimes used metaphorically to refer to the ratio of useful information to false or irrelevant data in a conversation or exchange. For example, in online discussion forums and other online communities, off-topic posts and spam are regarded as "noise" that interferes with the "signal" of appropriate discussion.BOOK,weblink 128, The Music Internet Untangled: Using Online Services to Expand Your Musical Horizons, Breeding, Andy, Giant Path, 2004, 9781932340020, The signal-to-noise ratio, the bandwidth, and the channel capacity of a communication channel are connected by the Shannonâ€“Hartley theorem.- the content below is remote from Wikipedia
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Definition
Signal-to-noise ratio is defined as the ratio of the power of a signal (meaningful information) to the power of background noise (unwanted signal):
or
mathrm{SNR} = frac{E[S^2]}{sigma^2_mathrm{N}}
where E refers to the expected value, i.e. in this case the mean of
S^2.
Decibels
Because many signals have a very wide dynamic range, signals are often expressed using the logarithmic decibel scale. Based upon the definition of decibel, signal and noise may be expressed in decibels (dB) as
P_mathrm{signal,dB} = 10 log_{10} left ( P_mathrm{signal} right )
and
P_mathrm{noise,dB} = 10 log_{10} left ( P_mathrm{noise} right ).
In a similar manner, SNR may be expressed in decibels as
Dynamic range
The concepts of signal-to-noise ratio and dynamic range are closely related. Dynamic range measures the ratio between the strongest un-distorted signal on a channel and the minimum discernible signal, which for most purposes is the noise level. SNR measures the ratio between an arbitrary signal level (not necessarily the most powerful signal possible) and noise. Measuring signal-to-noise ratios requires the selection of a representative or reference signal. In audio engineering, the reference signal is usually a sine wave at a standardized nominal or alignment level, such as 1 kHz at +4 dBu (1.228 VRMS).SNR is usually taken to indicate an average signal-to-noise ratio, as it is possible that (near) instantaneous signal-to-noise ratios will be considerably different. The concept can be understood as normalizing the noise level to 1 (0 dB) and measuring how far the signal 'stands out'.Difference from conventional power
In physics, the average power of an AC signal is defined as the average value of voltage times current; for resistive (non-reactive) circuits, where voltage and current are in phase, this is equivalent to the product of the rms voltage and current:
mathrm{P} = V_mathrm{rms}I_mathrm{rms}
Alternative definition
An alternative definition of SNR is as the reciprocal of the coefficient of variation, i.e., the ratio of mean to standard deviation of a signal or measurement:BOOK, Astronomical optics, D. J. Schroeder, 2nd, Academic Press, 1999, 978-0-12-629810-9, 433,weblink Bushberg, J. T., et al., The Essential Physics of Medical Imaging, (2e). Philadelphia: Lippincott Williams & Wilkins, 2006, p. 280.
mathrm{SNR} = frac{mu}{sigma}
where mu is the signal mean or expected value and sigma is the standard deviation of the noise, or an estimate thereof.The exact methods may vary between fields. For example, if the signal data are known to be constant, then sigma can be calculated using the standard deviation of the signal. If the signal data are not constant, then sigma can be calculated from data where the signal is zero or relatively constant. Notice that such an alternative definition is only useful for variables that are always non-negative (such as photon counts and luminance). It is commonly used in image processing,BOOK,weblink Digital image processing, 354, Rafael C. GonzÃ¡lez, Richard Eugene Woods, Prentice Hall, 2008, 0-13-168728-X, BOOK,weblink Image fusion: algorithms and applications, 471, Tania Stathaki, Academic Press, 2008, 0-12-372529-1, BOOK,weblink Multi-Sensor Data Fusion: Theory and Practice, Jitendra R. Raol, CRC Press, 2009, 1-4398-0003-0, BOOK,weblink The image processing handbook, John C. Russ, CRC Press, 2007, 0-8493-7254-2, where the SNR of an image is usually calculated as the ratio of the mean pixel value to the standard deviation of the pixel values over a given neighborhood. Sometimes SNR is defined as the square of the alternative definition above.This definition is closely related to the sensitivity index or d{{'}}, when assuming that the signal has two states separated by signal amplitude mu, and the noise standard deviation sigma does not change between the two states. The Rose criterion (named after Albert Rose) states that an SNR of at least 5 is needed to be able to distinguish image features with certainty. An SNR less than 5 means less than 100% certainty in identifying image details.BOOK, Rose, Albert, Vision â€“ Human and Electronic, Plenum Press, 9780306307324, 1973, 10,weblink [...] to reduce the number of false alarms to below unity, we will need [...] a signal whose amplitude is 4â€“5 times larger than the rms noise., Yet another alternative, very specific, and distinct definition of SNR is employed to characterize sensitivity of imaging systems; see Signal-to-noise ratio (imaging).Related measures are the "contrast ratio" and the "contrast-to-noise ratio".SNR for various modulation systems
Amplitude modulation
Channel signal-to-noise ratio is given by
mathrm{(SNR)_{C,AM}} = frac{A_C^2 (1 + k_a^2 P)} {2 W N_0}
where W is the bandwidth and k_a is modulation indexOutput signal-to-noise ratio (of AM receiver) is given by
mathrm{(SNR)_{O,AM}} = frac{A_c^2 k_a^2 P} {2 W N_0}
Frequency modulation
Channel signal-to-noise ratio is given by
mathrm{(SNR)_{C,FM}} = frac{A_c^2} {2 W N_0}
Output signal-to-noise ratio is given by
mathrm{(SNR)_{O,FM}} = frac{A_c^2 k_f^2 P} {2 N_0 W^3}
Improving SNR in practice
missing image!
- Analyse thermo gravimetrique bruit.png -
Recording of the noise of a thermogravimetric analysis device that is poorly isolated from a mechanical point of view; the middle of the curve shows a lower noise, due to a lesser surrounding human activity at night.
All real measurements are disturbed by noise. This includes electronic noise, but can also include external events that affect the measured phenomenon â€” wind, vibrations, gravitational attraction of the moon, variations of temperature, variations of humidity, etc., depending on what is measured and of the sensitivity of the device. It is often possible to reduce the noise by controlling the environment. Otherwise, when the characteristics of the noise are known and are different from the signals, it is possible to filter it or to process the signal.For example, it is sometimes possible to use a lock-in amplifier to modulate and confine the signal within a very narrow bandwidth and then filter the detected signal to the narrow band where it resides, thereby eliminating most of the broadband noise.When the signal is constant or periodic and the noise is random, it is possible to enhance the SNR by averaging the measurements. In this case the noise goes down as the square root of the number of averaged samples.Additionally, internal noise of electronic systems can be reduced by low-noise amplifiers.- Analyse thermo gravimetrique bruit.png -
Recording of the noise of a thermogravimetric analysis device that is poorly isolated from a mechanical point of view; the middle of the curve shows a lower noise, due to a lesser surrounding human activity at night.
Digital signals
When a measurement is digitized, the number of bits used to represent the measurement determines the maximum possible signal-to-noise ratio. This is because the minimum possible noise level is the error caused by the quantization of the signal, sometimes called quantization noise. This noise level is non-linear and signal-dependent; different calculations exist for different signal models. Quantization noise is modeled as an analog error signal summed with the signal before quantization ("additive noise").This theoretical maximum SNR assumes a perfect input signal. If the input signal is already noisy (as is usually the case), the signal's noise may be larger than the quantization noise. Real analog-to-digital converters also have other sources of noise that further decrease the SNR compared to the theoretical maximum from the idealized quantization noise, including the intentional addition of dither.Although noise levels in a digital system can be expressed using SNR, it is more common to use Eb/No, the energy per bit per noise power spectral density.The modulation error ratio (MER) is a measure of the SNR in a digitally modulated signal.Fixed point
{{see also|Fixed point arithmetic}}For n-bit integers with equal distance between quantization levels (uniform quantization) the dynamic range (DR) is also determined.Assuming a uniform distribution of input signal values, the quantization noise is a uniformly distributed random signal with a peak-to-peak amplitude of one quantization level, making the amplitude ratio 2n/1. The formula is then:Floating point
Floating-point numbers provide a way to trade off signal-to-noise ratio for an increase in dynamic range. For n bit floating-point numbers, with n-m bits in the mantissa and m bits in the exponent:Optical SNR
Optical signals have a carrier frequency that is much higher than the modulation frequency (about 200 THz and more). This way the noise covers a bandwidth that is much wider than the signal itself. The resulting signal influence relies mainly on the filtering of the noise. To describe the signal quality without taking the receiver into account, the optical SNR (OSNR) is used. The OSNR is the ratio between the signal power and the noise power in a given bandwidth. Most commonly a reference bandwidth of 0.1 nm is used. This bandwidth is independent of the modulation format, the frequency and the receiver. For instance an OSNR of 20 dB/0.1 nm could be given, even the signal of 40 GBit DPSK would not fit in this bandwidth. OSNR is measured with an optical spectrum analyzer.Types and abbreviations
Signal to noise ratio may be abbreviated as SNR and less commonly as S/N. PSNR stands for Peak signal-to-noise ratio. GSNR stands for Geometric Signal-to-Noise Ratio. SINR is the Signal-to-noise-plus-interference ratio.See also
{{Div col}}- Audio system measurements
- Generation loss
- Matched filter
- Near-far problem
- Noise margin
- Omega ratio
- Peak signal-to-noise ratio
- Signal-to-noise statistic
- Signal-to-noise-plus-interference ratio
- Signal to noise ratio (imaging)
- SINAD
- Subjective video quality
- Total harmonic distortion
- Video quality
Notes
{{Reflist|group="note"|1}}References
{{Reflist}}External links
- {{citation |title=Taking the Mystery out of the Infamous Formula,"SNR = 6.02N + 1.76dB," and Why You Should Care |author=Walt Kester |url=http://www.analog.com/static/imported-files/tutorials/MT-001.pdf |publisher=Analog Devices |access-date=2019-04-10}}
- ADC and DAC Glossary â€“ Maxim Integrated Products
- Understand SINAD, ENOB, SNR, THD, THD + N, and SFDR so you don't get lost in the noise floor â€“ Analog Devices
- weblink" title="web.archive.org/web/20060522134626weblink">The Relationship of dynamic range to data word size in digital audio processing
- Calculation of signal-to-noise ratio, noise voltage, and noise level
- Learning by simulations â€“ a simulation showing the improvement of the SNR by time averaging
- Dynamic Performance Testing of Digital Audio D/A Converters
- Fundamental theorem of analog circuits: a minimum level of power must be dissipated to maintain a level of SNR
- Interactive webdemo of visualization of SNR in a QAM constellation diagram Institute of Telecommunicatons, University of Stuttgart
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