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Analog to digital converter

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• NOWWe will b going to present on a topic Analog to Digital Converter..
• In this Presentation we will give an in-depth explanation about 1st.What is analog-to-digital conversion 2nd one is Sampling , which will b presented by Raj.3rd one is Quantization , By ShaileshAnd lastCode theory will b presented by Anurag .
• **********************************ASHUTOSH************************************Signals in the real world are analog: light sounds So, real-world signals must be converted into digital, using a circuit called ADC (Analog-to-Digital Converter).When we scan a picture with a scanner ..what the scanner is doing is an analog-to-digital conversion: it is taking the analog information provided by the picture (light) and converting into digital.When we record our voice we are using an analog-to-digital converter to convert our voice, which is analog, into digital..When an audio CD is recorded at a studio, once again analog-to-digital is taking place, converting sounds into digital numbers that will be stored on the disc.
• Whenever we need the analog signal back, the opposite conversion digital-to-analog, which is done by a circuit called DAC, Digital-to-Analog Converter is neededWhen you play an audio CD, what the CD player is doing is reading digital information stored on the disc and converting it back to analog so you can hear the music.But, why digital? There are some basic reasons to use digital signals instead of analog, noise being the number one.Since analog signals can assume any value, noise is interpreted as being part of the original signal.Digital systems, on the other hand, can only understand two numbers, zero and one. Anything different from this is discarded. Thats why you wont hear any unwanted noise when listening to an audio CD, even if you played it thousands of times before
• IF the message signal is coming from a digital source (e.g. a digital computer) then it is in the proper form for processing by a digital communication system.But this is not always the case . The message signal can be analog in nature (e.g. speech or video signal).In such a case it has to be converted into a discrete time signal . We use the sampling process to do this.
• Sampling is the process of converting a continuous analog signal to a discrete analog signal and the sampled signal is the discrete time representation of the original analog signal .Sampling means measuring the amplitude of the signal at equal intervals.Sampling means bifurcating(Breaking) down the continuous wave to a discrete set of points.Sampling is done by examining the wave at certain points and recording the values at those point’s.
• **************************************SHAILESH**********************************Zooming in, we see the sample values (on the vertical axis) at regular time intervals (the horizontal axis). Note that the numbers are not exact, but are rounded to the nearest whole number. For example, the second sample is between 13 and 14 volts, but it is rounded to 14. The sampling illustrated above produces a list of twelve 5-bit binary numbers, as shown below.
• Rate of frequency at which sampling occurs is known as sampling rate or sampling frequency , and denotes the number of sample taken per second or per inch . It determines the quality of output signalHigher the sampling rate more is the number of samples of the original wave that are obtained
• Digital audio is a computerized representation of real-life sounds. The quality of the audio is determined by the sample rate and bit depth at which the audio was captured. The higher the sample rate and bit depth (within reason!), the better the quality of the audio. Sample Rate refers to how many times per second the audio information is captured. Sample rates are measured in Kilohertz (KHz). 1 KHz equals 1000 samples per second. So, audio recorded at 44.1 KHz captures data at a rate of 44,100 samples per second. Most audio interfaces support sample rates of 44.1, 48, 88.2, and 96 KHz. Many higher-end devices also support 176.4 and 192 KHz sample rates as well. Bit Depth refers to how much information is captured with a sample. Each sample measures the amplitude (shape) of the wave, and higher bit depths allow the analog shape to be more closely matched
• . Imagine a piece of graph paper, on which you were trying to line up the graph with the smooth analog curve of a sine wave. The smaller the boxes on the graph (higher bit depth), the more closely you could match the shape of the sine wave.
• This theorem states that the sampling rate on analog-to-digital conversions must be at least two times the value of the highest frequency you want to capture.Since the human ear listens to sounds up to the frequency of 20 kHz, for music we need to use a sampling rate of at least 40,000 Hz. In fact, the CD uses a 44,100 Hz sampling rate, thus capturing more than our ears can hear (this value was arbitrated by Phillips and Sony when they created the CD). Some professional audio applications use an even higher sampling rate.The phone system, on the other hand, was created to transmit only human voice, which has a lower frequency range, up to 4 kHz. So on the digital part of the phone system, an 8,000 Hz sampling rate is used. Thats why if you try to transmit music through the phone the quality is bad: the phone circuitry cancels all frequencies above 4 kHz (ask a friend to put his/her phone near a stereo playing and you will hear what we are talking about).
• ************************************RAJ*****************************************The 2nd process of ANALOG TO DIGITAL CONVERSION involves Quantization.Quantization is a process of approximation or rounding off.The message signal is sampled &amp; amplitude of each sample is approximated {rounded off} to the nearest of a discrete levels called Quantization.Hence we decide on a particular level of quality required by us:Eg: Scan images In medical application needs to be of highest quality for proper diagnosis, but for a digital road map lower quality causes no harm.And this process of selecting a fewer numbers of amplitude levels from a large set is know as amplitude discretization.
• Quantization levels:Quantization levels refers to the number of different sample values that can be used to represent a digital quantity. image- few hundreds sample values from thousands Opting for higher values, we do get a better quality representation, but it will increase cost for storage &amp; processing of these values in computer.
• The process of approximation or rounding off is called as Quantization process.Quantizer converts the sampled signal into an approximate quantized signal which consists of only pre decided voltage level.Each sampled value at the input of the QuantizerIs approximated or rounded off to the nearest stabdard pre decided voltage levels. These levels are known as Quantization levels.
• After the quantization step , we have a set of sample values quantized to a specific number of levels , occurring at specific instant of time(or space). The amplitude levels of the samples are expressed as fraction of the difference between the minimum and maximum values. Code word generation involves expressing these amplitude levels in terms of binary codes or numbers , because that is finally how the data would be represented within a computer.The quantized samples are then converted to the digital signal In the form of a train or stream of binary digit 0 and 1 . Shown in fig
• 1]Optical fibers used to transmit digital signals are cheap &amp; easily available.3]Can connect several different users to the same link – such as video conferencing.
• 1] Digital signals need more ‘bandwidth to transmit the same information.2] The transmitter and receiver have to synchronize very carefully so that the information makes sense.
• Analog to digital converter

1. 1. Group members
2. 2. Analog to Digitalconverter
3. 3. Graphics
4. 4. 10010010
5. 5. 10010010 0’s And 1’s
6. 6. Analog to Digital conversion takes place in 3 steps:-1] SAMPLING: which measures the amplitude ofthe signal at equal interval. 2] Quantization: is the process of rounding of the signal to the nearest finite level.3Code word generation: finally converts the signalinto binary form. 100 100 101 001 010 000 101 1111
7. 7. If the message signalis coming from Then it is in the proper form for processing by a digital communication system In such a case it has to be converted into a discrete time signal . Sampling process
8. 8. Sampling is the process of converting a continuous analog signal to adiscrete analog signal and the sampled signal is the discrete timerepresentation of the original analog signal . Sampling Sample 1 2 3 4 5 6 7 8 9 10 11 12 Volts 10 14 16 16 14 10 6 2 0 0 2 6 Binary 01010 01110 10000 10000 01110 01010 00110 00010 00000 00000 00010 00110
9. 9. Sample 1 2 3 4 5 6 7 8 9 10 11 12Volts 10 14 16 16 14 10 6 2 0 0 2 6Binary 01010 01110 10000 10000 01110 01010 00110 00010 00000 00000 00010 00110
10. 10. Rate of frequency at which sampling occurs is known as samplingrate or sampling frequency , and denotes the number of sampletaken per second or per inch .It determines the quality of output signal
11. 11. Digital audioSample rate Bit depth Higher Better quality of audio 1 KHz = 1000 samples/second.Bit Depth refers to how much information is captured with asample. Each sample measures the amplitude (shape) of thewave, and higher bit depths allow the analog shape to be moreclosely matched.
12. 12. In the diagrams below, the X axis represents sample rate (eachline equals one sample) and the Y axis represents bit depth.At a low bit depth, the shape of At a low sample rate, thethe wave cannot be matched shape of the wave also cannotvery closely be matched very closelyAt a higher sample rate However, the higher theand bit depth, the shape of frequency of the sound, thethe wave can be more more difficult it is to closelyclosely matched. match the wave.
13. 13. This theorem states that the sampling rate on analog-to-digital conversions must be at least two times the value ofthe highest frequency you want to capture. Sampling Human ear For MUSIC rate 10000HZ 20 kHz 44100HZ Sampling rate
14. 14. The 2nd process of ANALOGTO DIGITAL CONVERSIONinvolves Quantization.Quantization is a process ofapproximation or rounding off.The message signal is sampled &amplitude of each sample isapproximated {rounded off} tothe nearest of a discrete levelscalled Quantization.
15. 15. Quantization levels refers to the number of differentsample values that can be used to represent a digitalquantity. To start with we may have thousands of sample valuesbut we may want to retain only a few hundreds ofthem.Opting for higher values, we do get a better qualityrepresentation, but it will increase cost for storage &processing of these values in computer.Hence we decide on a particular level of qualityrequired by us:
16. 16. Example: Scan images In medical application needs to be of highest quality for proper diagnosis, but for a digital road map lower quality causes no harm. And this process of selecting a fewer numbers of amplitude levels from a large set is know as amplitude discretization
17. 17. The process of approximation orrounding off is called asQuantization process.A device or algorithm functionthat performs Quantization iscalled Quantizer.The signal is approximated orrounded off to the neareststandard pre decided voltagelevels. These levels areknown as Quantizationlevels.
18. 18. Quantizer converts the sampled signal into an approximate quantized signal which consists of only pre decided voltage level.
19. 19. After the quantization step, the amplitudelevels obtained are expressed as fractionof the difference between the minimumand maximum values.Code word generation involves expressingthese amplitude levels in terms of binarycodes or numbers , because that is finallyhow the data would be represented withina computer.
20. 20. 1]Optical fibers2]Digital signals can be compressed so more channels can be transmitted along the same medium.3]Can connect several different usersto the same link eg: video conferencing4] Digital signals suffer less from noise because any errors can be detected and corrected using regenerators.
21. 21. 1. Need more bandwidth 2.
22. 22. The main applications of DSP are :1.Audio signal processing,2.Audio compression,3.Digital image processing,4.Video compression,5.Speech processing,6.Speech recognition,7.Digital communications,8.RADAR,9.Biomedicine