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Views: 33639 Engineering Made Easy
What is quantization and why it is needed in Digital signal processing is discussed in this part. By P. Madhan Mohan http://www.youtube.com/user/ThePowerDSP
Views: 94422 Madhan Mohan
http://AllSignalProcessing.com for more great signal-processing content: ad-free videos, concept/screenshot files, quizzes, MATLAB and data files. Real sampling systems use a limited number of bits to represent the samples of the signal, resulting in quantization of the signal amplitude to a limited set of values. The quantized values are then coded in a binary format for representation and storage in a digital system, such as a computer.
Views: 32074 Barry Van Veen
Quantization is explained with an example. A 2 bit quantizer is taken for explanation. By P.Madhan Mohan http://www.youtube.com/user/ThePowerDSP
Views: 51153 Madhan Mohan
Views: 46952 GATE ACHIEVERS
Views: 3070 David Dorran
Visit My BLOG for more Details- www.engineeringmadeeasypro.com This video explains Pulse Code Modulation (PCM). Pulse Code Modulation (PCM) is a type of pulse modulation technique. This video also includes quantization in pcm and sampling of the signal. Pulse modulation can be categorized broadly into two types- #Analog and #Digital The analog modulation can again be of two types- #Pulse Amplitude Modulation (PAM) #Pulse Time Modulation (PTM) The Pulse Time Modulation (PTM) can further be classified into two types of modulation- #Pulse Width Modulation (PWM)/Pulse Duration Modulation (PDM) #Pulse Position Modulation (PPM) Pulse Code Modulation (PCM) is a digital pulse modulation technique. You can see the classification of pulse modulation, Pulse Code Modulation (PCM) Now we will discuss the digital form of pulse modulation technique. This form of pulse modulation technique is known as Pulse Code Modulation (PCM). Pulse code modulation is a technique to convert analog signals into digital signals. After converting the signal into digital form, it becomes possible to transmit the digital signal through digital communication network and at the receiving end, it is converted back into it's original analog form. Pulse code modulation process involves the following three stages -#Sampling #Quantization and #Coding Sampling and Quantization of analog signal, sampling og signal, Quantization of signal Sampling and Quantization of analog signal this image shows the following- #Signal in its original analog form #The sampled signal obtained after sampling of this analog signal and #Quantized signal obtained after performing the quantization process. Now we are going to discuss, the process of sampling and quantization. During the discussion, please see the image carefully - The first waveform given in the image is of the analog signal, that we want to transmit over the digital communication network. But since it is in analog form, therefore first it needs to be converted into digital form. So to do this job, we take the help of Pulse Code Modulation (PCM). Sampling of signal The second part of this image, shows the sampled signal. In the process of sampling of the signal, we convert the continuous time signal into discrete time signal. You can see this conversion in the sampled signal shown in the image. The analog signal was continuous in time, since it had some value at every instant of time. But in the sampled signal, which is discrete in time, the value of the signal is present only at certain instants of time. Accuracy of the sampling increases with increase in frequency of the sampling. But some sampling error is introduced because of this sampling process, since it is not possible to have infinite sampling frequency practically. Sampling of the analog signal is performed with the help of sampling theorem. So let me define here, what is sampling theorem. Sampling Theorem:- A continuous-time signal can be completely represented in its samples and recovered back into its original form if the sampling frequency is greater than or equal to twice the highest frequency present in the modulating signal (message signal). It can be represented mathematically as- fs greater than or equal to 2fm Here 'fs' is the sampling frequency and 'fm' is the highest frequency present in the modulating signal. Quantization of Signal To understand the process of quantization look at the image given above. In the process of quantization, amplitude of the signal is cut horizontally into a number of fixed levels. Now the value of the signal is rounded-off (approximated) to the nearest level of amplitude. These certain levels of amplitude are shown in the image on the vertical axis. Here we have divided the amplitude range (peak to peak amplitude) into 'l' number of levels. The magnitude of each level is equal to the peak to peak amplitude range divided by the number of levels. It is important to note here that, quantized signal is just an approximation of the original signal. As the number of levels increases, the accuracy of quantization increases. Pulse Code Modulation (PCM) technique uses the process of quantization to convert analog signals into digital signals. Pulse Code Modulation Waveform The image given below shows pulse code modulated waveform. Pulse Code Modulation Waveform, Pulse Code Modulation, PCM waveform Pulse Code Modulation Waveform You can see in the image that PCM wave contains only two levels amplitude. These levels are represented by 0's and 1's. So it is clear that, here we have converted an analog signal having infinite number of levels of amplitude into just two levels of amplitude represented by 0's and 1's. Hence an analog signal has been converted into a digital signal. Pulse Modulation Techniques https://www.youtube.com/playlist?list=PLDp9Jik5WjRvjqQ6ruRFC6hZcxnOsp3BE #Modulation #modulationTechniques
Views: 18010 Engineering Made Easy
This is part two of my video series on Digital Audio. This Episode covering some more in depth aspects of the area. Watch Part 1 here: https://www.youtube.com/watch?v=W2-FP7twy8s Production Bytes Facebook Page: https://www.facebook.com/ProductionBytes Veranova's Music: http://www.facebook.com/OfficialVeranova Thanks for watching! Veranova
Views: 108344 Production Bytes
Views: 1509 David Dorran
Views: 269999 0612 TV w/ NERDfirst
Views: 81790 Gyaanism
http://www.fiberoptics4sale.com/wordpress/what-is-pulse-code-modulation-pcm/ http://www.fiberoptics4sale.com/wordpress/ In a brief sentence, pulse code modulation is a method used to convert an analog signal into a digital signal. So that it can be transmitted through a digital communication network, and then converted back into the original analog signal. The PCM process includes three steps: Sampling, Quantization, and Coding. In the sampling process, the magnitude of the analog signal is sampled regularly at uniform intervals. The obtained values are called samples. For a 4 kHz voice channel, the sampling rate is 8000 Hz, which means the signal is sampled 8000 times per second. The samples will then be converted to digital numbers as we will see in the quantization process. Quantization is the process of converting the obtained samples into discrete digital values. The most basic type of quantization is called uniform quantization. In an uniform quantization, the vertical axis, which represents the amplitude, is divided into equal sized steps. As shown in this figure, the range between 1 volt and -1 volt is divided into 16 steps, each step represents 0.125 volt. All the samples whose amplitude falls within an step, take the same step value. However, the quantization process introduces an error. This is because that the real amplitude of a sample is replaced by an approximate value. This error is called quantization noise or quantization distortion. In uniform quantization, the quantization distortion presents a problem. For example, let's assume a quantization error of 0.05 volt, if this happens at a high level signal, such as 5 volt, the noise ratio is 0.05 volt divided by 5 volt, which is 1%, not too bad. But if the same quantization error happens at a low level signal, such as 0.5 volt, the noise ratio is 0.05 volt divided by 0.5 volt, which is 10%. Simply put, for uniform quantization, the signal to noise ratio is good at high level signals, but bad at low level signals. That is why non-uniform quantization was introduced. In non-uniform quantization process, the steps are not of equal size. Small steps are used for small signal values and large steps for large values. The purpose of doing so is to achieve that the signal-to-noise ratio is nearly independent of the signal level. This is done by favoring low-level voice over higher-level voice. In other words, more code groups are assigned to speech at low levels than at the higher levels, progressively more as the level reduces. This is shown in this figure. There are two types of non-uniform quantization methods in popular use today. They are the A-law and the u-law. Let's first look at the A-law. A law follows the logarithmic formula listed here, with A equals to 87.6. We can see that the curve consists of linear piecewise segments, seven above and seven below the origin. The segment just above and the segment just below the origin consists of two linear segments. Counting the collinear elements by the origin, there are 16 segments. Each segment has 16 8-bit PCM codes assigned. These are the codewords that identify the voltage level of a sample at some moment in time. Each codeword, often called a PCM "word", consists of 8 bits. The first bit tells the receiver if the sample is a positive or negative voltage. We can see that all PCM words above the origin start with a binary 1, and those below the origin start with a binary 0. The next 3 bits in sequence identify the segment. There are eight segments above the origin and eight below the origin. The last 4 bits, shown as XXXX, indicate exactly where in a particular segment that voltage line is located. The second is called u-law. It follows the logarithmic formula listed here with u equals to 100. The North American T1 system uses the u-law quantization and coding process. The process is similar to that of A-law. Colin Yao Sales Manager Fiber Optics For Sale Co. 1532 Centre Pointe Dr. Milpitas, CA 95035 Web: http://www.fo4sale.com
Views: 228873 FOSCO CONNECT
Demostrates the effects of quantisation using an audio example
Views: 1320 David Dorran
Views: 16191 Knowledge in Depth
LECT-29: Quantization Process & Quantization noise
Views: 1718 EPOV CHANNEL
This presentation introduces the concept of quantisation error which arises during the capture of a discrete signal from a continuous signal
Views: 3807 David Dorran
A video by Jim Pytel for Renewable Energy Technology students at Columbia Gorge Community College
In this tutorial we understand the concept behind resolution of images. We explore the Sampling and Quantization problem and code the sampling using bi-linear interpolation using Matlab.
Views: 20649 rashi agrawal
PCM - method of analog to digital conversion Introduction Today my topic is Pulse Code Modulation or PCM- a method used to convert analog signals to digital signals. PCM consists of three steps: sampling, quantizing, and encoding. PCM may sound very complicated because it involves many big words, such as pulse, amplitude, modulation, sampling, sample rate, quantization or quantizing process, bit depth, and so so, but it is actually a very simple process if you take it apart and look closely one step a time. My topics are organized by playlists: https://www.youtube.com/user/sunnylearning/playlists My most popular videos: https://www.youtube.com/user/sunnylearning/videos?sort=p&view=0&flow=grid Wireless and Wi-Fi https://www.youtube.com/watch?v=PcbTMSf0D2M&list=PLSNNzog5eydvJG48PYnWnNY7-tQIfxTRb Remote Access/WAN technologies https://www.youtube.com/watch?v=B1tElYnFqL8&list=PLSNNzog5eyduTVeiVQRV_AM35YKSrFgzr This is my education channel. My topics cover networking, security, programming, data structure, algorithm, programming and other computer-related materials. Please leave comments, questions and subscribe! Thank you very much! Sunny Classroom
Views: 2821 Sunny Classroom
Lecture Series on Digital Communication by Prof.Bikash. Kumar. Dey , Department of Electrical Engineering,IIT Bombay. For more details on NPTEL visit http://nptel.iitm.ac.in
Views: 203978 nptelhrd
Views: 19843 Jonathan Valvano
Lecture Series on Digital Signal Processing by Prof.T.K.Basu, Department of Electrical Engineering, IIT Kharagpur. For more details on NPTEL visit http://nptel.iitm.ac.in
Views: 8052 nptelhrd
MIT MIT 6.003 Signals and Systems, Fall 2011 View the complete course: http://ocw.mit.edu/6-003F11 Instructor: Dennis Freeman License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu
Views: 19928 MIT OpenCourseWare
What is SNR and the importance of SNR is explained. The SNR equation is also derived. By Madhan Mohan http://www.youtube.com/user/ThePowerDSP
Views: 24749 Madhan Mohan
Here we derive the quantisation error.
http://adampanagos.org In the previous video we examined the impact of downsampling an audio signal. In this video, we examine the impact of changing the number of quantization levels used to store the signal amplitudes. An original WAV music file is loaded in Matlab that uses 8-bit quantization. The signal is then re-quantized to both 6-bit and 4-bit quantization levels and plotted to visualize the impact of fewer quantization levels on the signal. While signals with fewer quantization levels require less storage space, it comes at the cost of introducing additional quantization error. If you enjoyed my videos please "Like", "Subscribe", and visit http://adampanagos.org to setup your member account to get access to downloadable slides, Matlab code, an exam archive with solutions, and exclusive members-only videos. Thanks for watching!
Views: 2737 Adam Panagos
Audio out of sync with the beat? Audio quantizing to the rescue! Want to choose my next video!? Take the survey below! http://bit.ly/zOMDWD Skype: mpigsley7 Twitter: @logicalmitch
Views: 116601 Mitchel Pigsley
Alexander Knaub Institut of Telecommunications, University of Stuttgart http://webdemo.inue.uni-stuttgart.de/webdemos/02_lectures/uebertragungstechnik_1/sampling_theorem/
This video discusses quantization and related concepts, such as quantization error and LSB, with respect to the analog-to-digital converter. http://www.microchip.com/dataconverters
Views: 5955 Microchip Technology
Views: 7921 Engineering Made Easy
Definition of the signal to noise ratio (SNR) and simple computations with it. More instructional engineering videos can be found at http://www.engineeringvideos.org. This video is licensed under the Creative Commons BY-SA license http://creativecommons.org/licenses/by-sa/3.0/us/.
Views: 186644 Darryl Morrell
A lecture on the effects of sampling signals with fixed numbers of bits, and of rounding in binary arithmetic.
Views: 3156 Aaron Parsons
Lecture 40: In this lecture Prof Aditya K. Jagannatham of IIT Kanpur explains the following concepts in Principles of Communication Systems-I 1. Concept of Quantization. 2. Uniform Quantizer. 3. Mid-tread Quantizer.
Quantization (Signal Processing)In computer science, quantization is the process of splitting the set of continuous or discrete values into the finite number of intervals. Quantization is used in signal processing including audio/video compression processes. In the elementary quantization an integer value is divided into a natural number. Such number is called a quantization factor.In uniform (linear) quantization the set of values is split into equal intervals. In other words, an input value is divided by a constant value (quantization interval) and an integer part is taken from the quotient. Please, do not confuse quantization and discretization (and quantization interval with discretization interval respectively). In discretization a time-variable value (signal) is compared with a preset interval (discretization interval). Thus, in discretization the signal is split against the time component (horizontal component, as shown in the plot). Quantization brings signal to pre-set values by splitting it across the level (vertical component, as shown in the plot). Signal processed through quantization or discretization is called a digital signal.In signal digitization quantization level is also called a disretization depth or bit count. Discretization depth is measured in bits and stands for the number of bits specifying the signal amplitude. The higher discretiztion depth is, the more precisely a digital signal corresponds to an analogue one. In uniform quantization discretization depth is also called a dynamic range and measured in decibels (1 bit roughly corresponds to 6 dB).In level quantization sample values are represented by digital signals. In binary quantization the range of signal voltage from Umin to Umax is divided into 2n intervals. The value of yielded interval (quantization interval) is expressed by the formula.N-bit binary code, which is the number of interval expressed by a binary number is assigned to each interval. The code of the interval where the voltage of a sample lies is assigned to that signal sample. Thus, an analogue signal is represented through a sequence of binary numbers which correspond to the signal value in certain moments, i.e. by a digital signal. Note that each binary number is represented through a sequence of low and high-level pulses.
Views: 6423 ChipDipvideo
This video deals with basics of quantization process. After watching this video u can understand theoritically wat s quantization n its hapening. With this knowledge u can apply the same in solving advanced pblms. 0101=5 0110=6 http://www.facebook.com/vivekananda.tamil.3 U can visit this fb page. U can give ur fb id in coments box
Sampling and quantization and its applications to digital video signals.
Views: 928 Greg Durgin
Reason for choosing this topic is to clear the basic concepts used in all applications.
Codes: %Sampling Theorem clear all; close all; clc; f=input('Enter frequency'); %T=1/f; fs1=input('Enter the sampling frequency'); t=0:0.1:100; t1=0:10:500; x=sin(2*3.14*f*t); %2*pi*f*t subplot(2,1,1); plot(t,x); y=sin(2*3.14*f*t1/fs1); subplot(2,1,2); stem(t1,y); ------------------------------------------------------------- How to Sample an Analog signal in Matlab ADC DSP Digital Signal Processing Matlab Tutorial Matlab Basic Matlab for Beginner
Views: 26988 Sk Rezwan
Lecture Series on Digital Signal Processing by Prof.T.K.Basu, Department of Electrical Engineering, IIT Kharagpur. For more details on NPTEL visit http://nptel.iitm.ac.in
Views: 4044 nptelhrd
A video by Jim Pytel for Renewable Energy Technology students at Columbia Gorge Community College
Lecture 47: In this lecture Prof Aditya K. Jagannatham of IIT Kanpur explains the following concepts in Principles of Communication Systems-I 1. Introduction to Differential Pulse Coded Modulation. . 2. Quantization and Signal Reconstruction in DPCM. 3. DPCM schematic diagrams.
Continuation of a lecture on the effects of sampling signals with fixed numbers of bits, and of rounding in binary arithmetic.
Views: 740 Aaron Parsons
An A Level Physics revision video covering Digital Sampling, Signal Spectra and Bandwidth
Views: 47700 DrPhysicsA
Views: 5192 itechnica
This video runs over the basics of signal sampling and analog to digital conversion. Watch the next part of this at: https://www.youtube.com/watch?v=zZAk0sKI0VY The video was created as part of the Khan Academy Talent Search. #khanacademytalentsearch
Views: 4570 Adrian Henry
VLSI Data Conversion Circuits by Dr. Shanthi Pavan, Department of Electrical Engineering, IIT Madras. For more details on NPTEL visit http://nptel.iitm.ac.in
Views: 5100 nptelhrd
An overview of the Quantize functions in Pro Tools and how they can be used to modify the timing of both audio and MIDI data.
Views: 58394 Eric Kuehnl
sampling and quantization in digital image processing
Views: 12645 Last Night Study