Random energy model: Difference between revisions

From formulasearchengine
Jump to navigation Jump to search
en>BattyBot
en>Bibcode Bot
m Adding 0 arxiv eprint(s), 1 bibcode(s) and 0 doi(s). Did it miss something? Report bugs, errors, and suggestions at User talk:Bibcode Bot
 
Line 1: Line 1:
[[File:4-bit-linear-PCM.svg|thumb|An analogue signal (in red) encoded to 4-bit PCM digital samples (in blue); the bit depth is 4, so each sample's amplitude is one of 16 possible values.]]
Hi there, I am Andrew Berryhill. Distributing production is where her main income comes from. For years she's been living in Kentucky but her spouse wants them to move. I am really fond of to go to karaoke but I've been taking on new issues recently.<br><br>my web-site :: clairvoyant psychic ([http://www.seekavideo.com/playlist/2199/video/ http://www.seekavideo.com/playlist/2199/video/])
 
In [[digital audio]] using [[pulse-code modulation]] (PCM), '''bit depth''' is the number of [[bit]]s of information in each [[Sampling (signal processing)|sample]], and it directly corresponds to the '''resolution''' of each sample. Examples of bit depth include [[Compact Disc Digital Audio]], which uses 16 bits per sample, and [[DVD-Audio]] and [[Blu-ray Disc]] which can support up to 24 bits per sample.
 
In basic implementations, variations in bit depth primarily affect the noise level from [[quantization error]]—thus the [[signal-to-noise ratio]] (SNR) and [[dynamic range]]. However, techniques such as [[dither]]ing, [[noise shaping]] and [[oversampling]] mitigate these effects without changing the bit depth. Bit depth also affects [[bit rate]] and file size.
 
Bit depth is only meaningful in reference to a PCM [[digital signal]]. Non-PCM formats, such as [[lossy compression]] formats like [[MP3]], [[Advanced Audio Coding|AAC]] and [[Vorbis]], do not have associated bit depths. For example, in MP3, quantization is performed on PCM samples that have been transformed into the [[frequency domain]].
 
== Binary resolution ==
A PCM signal is a sequence of digital audio samples containing the data providing the necessary information to [[Signal reconstruction|reconstruct]] the original [[analog signal]]. Each sample represents the [[amplitude]] of the signal at a specific point in time, and the samples are uniformly spaced in time. The amplitude is the only information explicitly stored in the sample, and it is typically stored as either an [[integer]] or a [[floating point]] number, encoded as a [[binary number]] with a fixed number of digits: the sample's ''bit depth''.
 
The resolution of binary integers increases [[Exponentiation|exponentially]] as the word length increases. Adding one bit doubles the resolution, adding two quadruples it and so on. The number of possible values that can be represented by an integer bit depth can be calculated by using [[Power of two|2<sup>''n''</sup>]], where ''n'' is the bit depth.<ref name="Understanding Audio">Thompson, Dan (2005). ''Understanding Audio''. Berklee Press. ISBN 978-0-634-00959-4.</ref> Thus, a [[16-bit]] system has a resolution of 65,536 (2<sup>16</sup>) possible values.
 
PCM audio data is typically stored as [[Signedness|signed]] numbers in [[two's complement]] format.<ref name="Julius PCM">{{cite web | url=https://ccrma.stanford.edu/~jos/mdft/Pulse_Code_Modulation_PCM.html | title=Pulse Code Modulation (PCM) | author=Smith, Julius | year=2007 | work=Mathematics of the Discrete Fourier Transform (DFT) with Audio Applications, Second Edition, online book | accessdate= 22 October 2012}}</ref>
 
=== Floating point ===
Many audio [[file format]]s and [[digital audio workstation]]s (DAWs) now support PCM formats with samples represented by [[floating point]] numbers. Both the [[WAV]] file format and the [[Audio Interchange File Format|AIFF]] file format support floating point PCM<ref name="waveref">{{cite web |url=http://www-mmsp.ece.mcgill.ca/documents/AudioFormats/WAVE/WAVE.html |title=Audio File Format Specifications, WAVE Specifications |author=Kabal, Peter |date=3 January 2011 |publisher=McGill University |accessdate=10 August 2013}}</ref><ref name="aiffref">{{cite web |url=http://www-mmsp.ece.mcgill.ca/Documents/AudioFormats/AIFF/AIFF.html |title=Audio File Format Specifications, AIFF / AIFF-C Specifications |author=Kabal, Peter |date=3 January 2011 |publisher=McGill University |accessdate=10 August 2013}}</ref> and major DAWs such as [[Pro Tools]], [[Reason (software)|Reason]], [[FL Studio]], and [[Ableton Live]] support varied floating point processing capabilities.<ref name="ptnativefloat">{{cite book |url=http://books.google.com/books?id=0WEKAAAAQBAJ&lpg=PA239&pg=PA247#v=onepage&q&f=false |title=Pro Tools 10 Advanced Music Production Techniques, pg. 247 |author=Campbell, Robert |year=2013 |publisher=Cengage Learning |accessdate=12 August 2013}}</ref><ref name="protools10float">{{cite web |url=http://www.soundonsound.com/sos/mar12/articles/pt-10.htm |title=Avid Pro Tools 10 |author=Wherry, Mark |date=March 2012 |publisher=Sound On Sound |accessdate=10 August 2013}}</ref><ref name="reasonfloat">{{cite web |url=http://www.soundonsound.com/sos/oct05/articles/reasontechnique.htm |title=Reason Mixing Masterclass |author=Price, Simon |date=October 2005 |publisher=Sound On Sound |accessdate=10 August 2013}}</ref><ref name="live9manual">{{cite web | url=https://www.ableton.com/en/manual/mixing/ | title=Ableton Reference Manual Version 9, 15. Mixing | publisher=Ableton | year=2013 | accessdate=26 August 2013}}</ref>
 
Unlike integers, whose bit pattern is a single series of bits, a floating point number is instead composed of separate fields whose mathematical relation forms a number. The most common standard is [[IEEE floating point]] which is composed of three bit patterns: a [[sign bit]] which represents whether the number is positive or negative, an exponent and a [[Significand|mantissa]] which is raised by the exponent. The mantissa is expressed as a [[Binary number#Fractions|binary fraction]] in IEEE base two floating point formats.<ref name="dspguide4">{{cite web |url=http://www.dspguide.com/ch4/3.htm |title=The Scientist and Engineer's Guide to Digital Signal Processing, Chapter 4 – DSP Software / Floating Point (Real Numbers) |author=Smith, Steven |year=1997-1998 |website=www.dspguide.com |accessdate=10 August 2013}}</ref>
 
== Quantization ==
The bit depth limits the [[signal-to-noise ratio]] (SNR) of the reconstructed signal to a maximum level determined by [[Quantization (signal processing)|quantization]] error. The bit depth has no impact on the [[frequency response]], which is constrained by the [[sample rate]].
 
Quantization noise is a [[Model (abstract)|model]] of quantization error introduced by the [[Sampling (signal processing)|sampling]] process during [[Analog-to-digital converter|analog-to-digital conversion]] (ADC). It is a rounding error between the analog input voltage to the ADC and the output digitized value. The noise is [[Nonlinear system|nonlinear]] and signal-dependent.
 
[[Image:Least significant bit.svg|thumb|280px|right|An [[8-bit]] binary number of the base ten value 149 with the LSB highlighted.]]
 
In an ideal ADC, where the quantization error is uniformly distributed between <math>\scriptstyle{\pm \frac{1}{2}}</math> [[least significant bit]] (LSB) and where the signal has a uniform distribution covering all quantization levels, the [[signal-to-quantization-noise ratio]] (SQNR) can be calculated from
 
:<math>\mathrm{SQNR} = 20 \log_{10}(2^Q) \approx 6.02 \cdot Q\ \mathrm{dB} \,\!</math>
 
where Q is the number of quantization bits and the result is measured in [[decibel]]s (dB).<ref>See [[Signal-to-noise ratio#Fixed point]])</ref><ref>{{cite web |url=http://www.analog.com/static/imported-files/tutorials/MT-001.pdf |title=Taking the Mystery out of the Infamous Formula, "SNR = 6.02N + 1.76dB," and Why You Should Care |author= Walt Kester |publisher=[[Analog Devices]] |year=2007 |accessdate=26 July 2011| archiveurl= http://web.archive.org/web/20110616182255/http://www.analog.com/static/imported-files/tutorials/MT-001.pdf| archivedate= 16 June 2011 <!--DASHBot-->| deadurl= no}}</ref>
 
[[24-bit]] digital audio has a theoretical maximum SNR of 144&nbsp;dB, compared to 96&nbsp;dB for 16-bit; however, {{asof|2007|lc=on}} digital audio converter technology is limited to a SNR of about 124&nbsp;dB (21-bit)<ref>{{cite web |url=http://focus.ti.com/docs/prod/folders/print/pcm4222.html |title=PCM4222 |accessdate=21 April 2011}}</ref> because of real-world limitations in [[integrated circuit]] design. Still, this approximately matches the performance of the human [[auditory system]].<ref>{{cite web |url=http://media.paisley.ac.uk/~campbell/AASP/Aspects%20of%20Human%20Hearing.PDF |title=Aspects of Human Hearing |author=D. R. Campbell |quote=The dynamic range of human hearing is [approximately] 120&nbsp;dB |accessdate=21 April 2011}}</ref><ref>{{cite web |url=http://hyperphysics.phy-astr.gsu.edu/hbase/sound/earsens.html#c2 |quote=The practical dynamic range could be said to be from the threshold of hearing to the threshold of pain [130&nbsp;dB] |title=Sensitivity of Human Ear |accessdate=21 April 2011| archiveurl= http://web.archive.org/web/20110604105752/http://hyperphysics.phy-astr.gsu.edu/hbase/sound/earsens.html| archivedate= 4 June 2011 <!--DASHBot-->| deadurl= no}}</ref>
 
{| class="wikitable"
|+ Signal-to-noise ratio and resolution of bit depths
! # bits !! SNR !! Possible integer values !! Base ten signed range
|-
!4
| 24.08 dB || 16 || −8 to +7
|-
!8
| 48.16 dB || 256 || −128 to +127
|-
!11<ref>This is the bit depth that the [[Raspberry Pi]] uses when driving the [[Pulse-width modulation|pulse-width modulator]] of its BCM2835 chip</ref>
| 66.22 dB || 2048 || −1024 to +1023
|-
!16
| 96.33 dB || 65,536 || −32,768 to +32,767
|-
!20
| 120.41 dB || 1,048,576 || −524,288 to +524,287
|-
!24
| 144.49 dB || 16,777,216 || −8,388,608 to +8,388,607
|-
!32
| 192.66 dB || 4,294,967,296 || −2,147,483,648 to +2,147,483,647
|-
!48
| 288.99 dB || 281,474,976,710,656 || −140,737,488,355,328 to +140,737,488,355,327
|-
!64
| 385.32 dB || 18,446,744,073,709,551,616 || −9,223,372,036,854,775,808 to +9,223,372,036,854,775,807
|}
 
The resolution of floating point samples is less straightforward than integer samples, but the benefit comes in the increased accuracy of low values. In floating point representation, the space between any two adjacent values is of the same proportion as the space between any other two adjacent values, whereas in an integer representation, the space between adjacent values gets larger in proportion to low-level signals. This greatly increases the SNR because the accuracy of a high-level signal will be the same as the accuracy of an identical signal at a lower level.<ref name="dspguide28">{{cite web |url=http://www.dspguide.com/ch28/4.htm |title=The Scientist and Engineer's Guide to Digital Signal Processing, Chapter 28 – Digital Signal Processors / Fixed versus Floating Point |author=Smith, Steven |year=1997–1998 |website=www.dspguide.com |accessdate=10 August 2013}}</ref>
 
The trade-off between floating point and integers is that the space between large floating point values is greater than the space between large integer values of the same bit depth. Rounding a large floating point number results in a greater error than rounding a small floating point number whereas rounding an integer number will always result in the same level of error. In other words, integers have round-off that is uniform, always rounding the LSB to 0 or 1, and floating point has SNR that is uniform, the quantization noise level is always of a certain proportion to the signal level.<ref name="dspguide28" /> A floating point noise floor will rise as the signal rises and fall as the signal falls, resulting in audible variance if the bit depth is low enough.<ref name="48forproaudio">{{cite web |url=http://www.jamminpower.com/PDF/48-bit%20Audio.pdf |title=48-Bit Integer Processing Beats 32-Bit Floating-Point for Professional Audio Applications |author=Moorer, James |date=September 1999 |website=www.jamminpower.com |accessdate=12 August 2013}}</ref>
 
=== Audio processing ===
Most processing operations on digital audio involve requantization of samples, and thus introduce additional rounding error analogous to the original quantization error introduced during analog to digital conversion. To prevent rounding error larger than the implicit error during ADC, calculations during processing must be performed at higher precisions than the input samples.<ref name="wordrelation">{{cite web| url=http://www.analog.com/en/content/relationship_data_word_size_dynamic_range/fca.html |title=THE RELATIONSHIP OF DATA WORD SIZE TO DYNAMIC RANGE AND SIGNAL QUALITY IN DIGITAL AUDIO PROCESSING APPLICATIONS |author=Tomarakos, John |publisher=Analog Systems |website=www.analog.com |accessdate=16 August 2013 }}</ref>
 
[[Digital signal processing]] (DSP) operations can be performed in either [[Fixed-point arithmetic|fixed point]] or floating point precision. In either case, the precision of each operation is determined by the precision of the hardware operations used to perform each step of the processing and not the resolution of the input data. For example, on [[x86]] processors, floating point operations are performed at 32- or 64-bit precision and fixed point operations at 16-, 32- or 64-bit resolution. Consequently, all processing performed on Intel-based hardware will be performed at 16-, 32- or 64-bit integer precision, or 32- or 64-bit floating point precision regardless of the source format. However, if memory is at a premium, software may still choose to output lower resolution 16- or 24-bit audio after higher precision processing.
 
Fixed point [[digital signal processor]]s often support unusual word sizes and precisions in order to support specific signal resolutions. For example, the [[Motorola 56000]] DSP chip uses 24-bit word sizes, 24-bit multipliers and 56-bit accumulators to perform [[multiply-accumulate operation]]s on two 24-bit samples without overflow or rounding.<ref>{{cite web|title=DSP56001A|url=http://cache.freescale.com/files/dsp/doc/inactive/DSP56001A.pdf|publisher=Freescale|accessdate=15 August 2013}}</ref> On devices that do not support large accumulators, fixed point operations may be implicitly rounded, reducing precision to below that of the input samples.
 
Errors compound through multiple stages of DSP at a rate that depends on the operations being performed. For uncorrelated processing steps on audio data without a DC offset, errors are assumed to be random with zero mean. Under this assumption, the standard deviation of the distribution represents the error signal, and quantization error scales with the square root of the number of operations.<ref>{{cite web|last=Smith|first=Steven|title=he Scientist and Engineer's Guide to Digital Signal Processing|url=http://www.dspguide.com/ch4/4.htm|work=Ch. 4|accessdate=19 August 2013}}</ref> High levels of precision are necessary for algorithms that involve repeated processing, such as [[convolution]].<ref name="wordrelation"/> High levels of precision are also necessary in recursive algorithms, such as [[infinite impulse response]] (IIR) filters.<ref>{{cite journal|last=Carletta|first=Joan|title=Determining Appropriate Precisions for Signals in Fixed-Point IIR Filters|journal=DAC|year=2003|url=http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.92.1266&rep=rep1&type=pdf|accessdate=15 August 2013}}</ref> In the particular case of IIR filters, rounding error can degrade frequency response and cause instability.<ref name="wordrelation"/>
 
== Dither ==
{{main|Dither}}
The noise introduced by quantization error, including rounding errors and loss of precision introduced during audio processing, can be mitigated by adding a small amount of random noise, called [[dither]], to the signal before quantizing. Dithering eliminates the granularity of quantization error, giving very low distortion, but at the expense of a slightly raised [[noise floor]]. Measured using [[ITU-R 468 noise weighting]], this is about 66&nbsp;dB below [[alignment level]], or 84&nbsp;dB below digital [[full scale]], which is somewhat lower than the microphone noise level on most recordings, and hence of no consequence in 16-bit audio (see [[Programme level]] for more on this).
 
24-bit audio does not require dithering, as the noise level of the digital converter is always louder than the required level of any dither that might be applied. 24-bit audio could theoretically encode 144 dB of dynamic range, but no ADCs exist that can provide higher than ~125 dB.<ref>[http://skywired.net/blog/2011/09/choosing-high-performance-audio-adc/ Choosing a high-performance audio ADC] - "I went looking for the best dynamic range audio ADC I could find" and highest are 123 dB dynamic range</ref>
 
Dither can also be used to increase the effective dynamic range. The ''perceived'' dynamic range of 16-bit audio can be as high as 120 dB with noise-shaped [[dither]], taking advantage of the frequency response of the human ear.<ref>{{cite web |url=https://www.xiph.org/~xiphmont/demo/neil-young.html |title=24/192 Music Downloads ...and why they make no sense |last=Montgomery |first=Chris |authorlink=Chris Montgomery |date=March 25, 2012 |website=xiph.org |accessdate=26 May 2013 |quote=With use of shaped dither, which moves quantization noise energy into frequencies where it's harder to hear, the effective dynamic range of 16 bit audio reaches 120dB in practice, more than fifteen times deeper than the 96dB claim. 120dB is greater than the difference between a mosquito somewhere in the same room and a jackhammer a foot away.... or the difference between a deserted 'soundproof' room and a sound loud enough to cause hearing damage in seconds. 16 bits is enough to store all we can hear, and will be enough forever.}}</ref>
 
== Dynamic range ==
[[Dynamic range]] is the difference between the largest and smallest signal a system can record or reproduce. Without dither, the dynamic range correlates to the quantization noise floor. For example, 16-bit integer resolution allows for a dynamic range of about 96&nbsp;dB.
 
Using higher bit depths during [[Recording studio|studio recording]] accommodates greater dynamic range. If the signal's dynamic range is lower than that allowed by the bit depth, the recording has [[Headroom (audio signal processing)|headroom]], and the higher the bit depth, the more headroom that's available. This reduces the risk of [[Clipping (audio)|clipping]] without encountering quantization errors at low volumes.
 
With the proper application of dither, digital systems can reproduce signals with levels lower than their resolution would normally allow, extending the effective dynamic range beyond the limit imposed by the resolution.<ref>{{cite web |url=http://www.e2v.com/assets/media/files/documents/broadband-data-converters/doc0869B.pdf |title=Dithering in Analog-to-Digital Conversion |publisher=e2v Semiconductors |year=2007 |accessdate=26 July 2011}}</ref>
 
The use of techniques such as [[oversampling]] and [[noise shaping]] can further extend the dynamic range of sampled audio by moving quantization error out of the frequency band of interest.
 
=== Oversampling ===
{{Main|Oversampling}}
 
Oversampling is an alternative method to increase the dynamic range of PCM audio without changing the number of bits per sample.<ref>{{cite web|last=Kester|first=Walt|title=Oversampling Interpolating DACs|url=http://www.analog.com/static/imported-files/tutorials/MT-017.pdf|publisher=Analog Devices|accessdate=19 August 2013}}</ref> In oversampling, audio samples are acquired at a multiple of the desired sample rate. Because quantization error is assumed to be uniformly distributed with frequency, much of the quantization error is shifted to ultrasonic frequencies, and can be removed by the [[digital to analog converter]] during playback.
 
For an increase equivalent to ''n'' additional bits of resolution, a signal must be oversampled by
 
:<math> \mathrm{number\ of\ samples} = (2^n)^2 = 2^{2n}.</math>
 
For example, a 14-bit ADC can produce 16-bit 48&nbsp;kHz audio if operated at 16x oversampling, or 768&nbsp;kHz. Oversampled PCM therefore exchanges fewer bits per sample for more samples in order to obtain the same resolution.
 
=== Noise shaping ===
{{Main|Noise shaping}}
 
Oversampling a signal results in equal quantization noise per unit of bandwidth at all frequencies and a dynamic range that improves with only the square root of the oversampling ratio. Noise shaping is a technique that adds additional noise at higher frequencies which cancels out some error at lower frequencies, resulting in a larger increase in dynamic range when oversampling. For ''n''th-order noise shaping, the dynamic range of an oversampled signal is improved by an additional 6''n''&nbsp;dB relative to oversampling without noise shaping.<ref>{{cite web|title=B.1 First and Second-Order Noise Shaping Loops|url=http://www.iue.tuwien.ac.at/phd/schrom/node115.html|accessdate=19 August 2013}}</ref> For example, for a 20&nbsp;kHz analog audio sampled at 4x oversampling with second order noise shaping, the dynamic range is increased by 30&nbsp;dB. Therefore a 16-bit signal sampled at 176&nbsp;kHz would have equal resolution as a 21-bit signal sampled at 44.1&nbsp;kHz without noise shaping.
 
Noise shaping is commonly implemented with [[delta-sigma modulation]]. Using delta-sigma modulation, [[Super Audio CD]] obtains 120&nbsp;dB SNR at audio frequencies using 1-bit audio with 64x oversampling.
 
== Applications ==
Bit depth is a fundamental property of digital audio implementations and there are a variety of situations where it is a measurement.
 
{| class="wikitable"
|+ style="padding: 6px;" | Example applications and bits per sample
! style="padding: 6px; border-bottom: 3px solid darkgray;" | Application !! style="padding: 6px; border-bottom: 3px solid darkgray;" | Description !! style="padding: 6px; border-bottom: 3px solid darkgray;" | Audio format(s)
|-
! style="text-align: left; background: #f6f6f6;" | [[Compact Disc Digital Audio|CD-DA]] (Red Book)<ref name="cdda">{{cite web | url=http://www.sweetwater.com/sweetcare/articles/masterlink-what-red-book-cd/ | title=Sweetwater Knowledge Base, Masterlink: What is a "Red Book" CD? | publisher=Sweetwater | date=27 April 2007 | website=www.sweetwater.com | accessdate=25 August 2013}}</ref>
| Digital media || 16-bit [[Linear pulse-code modulation|LPCM]]
|-
! style="text-align: left; background: #f6f6f6;" | [[DVD-Audio]]<ref name="dvdaudio">{{cite web |url=http://web.archive.org/web/20120304060434/http://patches.sonic.com/pdf/white-papers/wp_dvd_audio.pdf |title=Understanding DVD-Audio |publisher=Sonic Solutions |format=PDF |accessdate=25 August 2013 }}</ref>
| Digital media || 16-, 20- and 24-bit LPCM<ref group=note>DVD-Audio also supports optional [[Meridian Lossless Packing]], a [[lossless compression]] scheme.</ref>
|-
! style="text-align: left; background: #f6f6f6;" | Super Audio CD<ref name="surround">{{cite web | url=http://www.extremetech.com/computing/48844-surround-sound/10 | title=Surround Sound, Page 10 | author=Shapiro, L. | publisher=ExtremeTech | date=2 July 2001 | accessdate=26 August 2013}}</ref>
| Digital media || 1-bit [[Direct Stream Digital]] ([[Pulse-density modulation|PDM]])
|-
! style="text-align: left; background: #f6f6f6;" | [[Blu-ray Disc#Audio|Blu-ray Disc audio]]<ref name="bluray">{{cite web| url=http://www.blu-raydisc.com/assets/Downloadablefile/BD-ROM-AV-WhitePaper_100423-17830.pdf | title=White paper Blu-ray Disc Format, 2.B Audio Visual Application Format Specifications for BD-ROM Version 2.4 |date=April 2010 | publisher = Blu-ray Disc Association | format=PDF | accessdate=25 August 2013}}</ref>
| Digital media || 16-, 20- and 24-bit LPCM and others<ref group=note>Blu-ray supports a variety of non-LPCM formats but all conform to some combination of 16, 20 and 24 bits per sample.</ref>
|- style="border-bottom: 2px solid darkgray;"
! style="text-align: left; background: #f6f6f6;"| [[DV]] audio<ref name="dvaudio">{{cite web | url=http://www.stanford.edu/~hbreit/CILECT/DV_Report.htm | title=DV – A SUCCESS STORY | author=Puhovski, Nenad |date=April 2000 | website=www.stanford.edu | accessdate=26 August 2013}}</ref>
| Digital media || 12-bit compressed PCM and 16-bit uncompressed PCM
|-
! style="text-align: left; background: #f6f6f6;" | [[ITU-T]] Recommendation [[G.711]]<ref name="g711">{{cite web | url=http://www.itu.int/rec/T-REC-G.711-198811-I/en | title=G.711 : Pulse code modulation (PCM) of voice frequencies | publisher=International Telecommunications Union | format=PDF | accessdate=25 August 2013}}</ref>
| Compression standard for [[telephony]] || 8-bit PCM with [[companding]]<ref group=note>ITU-T specifies the [[A-law algorithm|A-law]] and [[μ-law algorithm|μ-law]] companding algorithms, compressing down from 13 and 14 bits respectively.</ref>
|- style="border-bottom: 2px solid darkgray;"
! style="text-align: left; background: #f6f6f6;" | [[NICAM]]-1, NICAM-2 and NICAM-3<ref name="nicam">{{cite web | url=http://web.archive.org/web/20121108045757/http://downloads.bbc.co.uk/rd/pubs/reports/1978-26.pdf | title=DIGITAL SOUND SIGNALS: tests to compare the performance of five companding systems for high-quality sound signals | publisher=BBC Research Department |date=August 1978 | accessdate=26 August 2013}}</ref>
| Compression standards for [[broadcasting]] || 10-, 11- and 10-bit PCM respectively, with companding<ref group=note>NICAM systems 1, 2 and 3 compress down from 13, 14 and 14 bits respectively.</ref>
|-
! style="text-align: left; background: #f6f6f6;" | Pro Tools 11<ref name="ptdocs">{{cite web | url=http://avid.force.com/pkb/articles/en_US/User_Guide/Pro-Tools-11-Documentation | title=Pro Tools Documentation, Pro Tools Reference Guide | publisher=Avid | year=2013 | format=ZIP/PDF | accessdate=26 August 2013}}</ref>
| DAW by [[Avid Technology]] || 16- and 24-bit or 32-bit floating point sessions and 64-bit floating point [[Audio mixing (recorded music)|mixing]]
|-
! style="text-align: left; background: #f6f6f6;" | [[Logic Pro]] X<ref name="logicxguide">{{cite web | url=http://manuals.info.apple.com/en_US/logic_pro_x_user_guide.pdf | title=Logic Pro X - User Guide | publisher=Apple |date=January 2010 | format=PDF | accessdate=26 August 2013}}</ref>
| DAW by [[Apple Inc.]] || 16- and 24-bit projects
|-
! style="text-align: left; background: #f6f6f6;" | [[GarageBand]] '11 (version 6)<ref name="garageband">{{cite web | url=http://support.apple.com/kb/PH1873 | title=GarageBand '11: Set the audio resolution | publisher=Apple | date=13 March 2012 | accessdate=26 August 2013}}</ref>
| DAW by Apple Inc. || 16-bit default with 24-bit real instrument recording
|-
! style="text-align: left; background: #f6f6f6;" | Live 9<ref name="live9manual"/>
| DAW by [[Ableton]] || 32-bit floating point mixing
|- style="border-bottom: 2px solid darkgray;"
! style="text-align: left; background: #f6f6f6;" | Reason 7<ref name="reasonmanual">{{cite web | url=http://dl.propellerheads.se/Reason7/Manuals/Reason_7_Operation_Manual.pdf | title=Reason 7 Operation Manual | publisher=Propellerhead Software | year=2013 | format=PDF | accessdate=26 August 2013}}</ref>
| DAW by [[Propellerhead Software]] || 16-, 20- and 24-bit I/O, 32-bit floating point arithmetic and 64-bit summing
|}
 
== Bit rate and file size ==
Bit depth affects [[bit rate]] and file size. Bit rate refers to the amount of data, specifically bits, transmitted or received per second.
 
== See also ==
*[[Audio system measurements]]
*[[Color depth]]—corresponding concept for digital images
*[[Effective number of bits]]
 
== Notes ==
{{reflist|group=note}}
 
== References ==
{{Reflist}}
*{{cite book |title=Principles of Digital Audio |edition=4th |author=Ken C. Pohlmann |publisher=McGraw-Hill Professional |isbn=978-0-07-134819-5 |date=15 February 2000}}
 
[[Category:Digital audio]]

Latest revision as of 08:48, 10 July 2014

Hi there, I am Andrew Berryhill. Distributing production is where her main income comes from. For years she's been living in Kentucky but her spouse wants them to move. I am really fond of to go to karaoke but I've been taking on new issues recently.

my web-site :: clairvoyant psychic (http://www.seekavideo.com/playlist/2199/video/)