SlideShare a Scribd company logo
1 of 44
15EE55C – DIGITAL SIGNAL PROCESSING AND
ITS APPLICATIONS
INTRODUCTION
Dr. M. Bakrutheen AP(SG)/EEE
Mr. K. Karthik Kumar AP/EEE
DEPARTMENT OF ELECTRICAL AND ELECTRONICS ENGINEERING
NATIONAL ENGINEERING COLLEGE, K.R. NAGAR, KOVILPATTI – 628 503
(An Autonomous Institution, Affiliated to Anna University – Chennai)
INTRODUCTION
 Most of the signals directly encountered in science and engineering are
continuous: light intensity that changes with distance; voltage that
varies over time; a chemical reaction rate that depends on temperature,
etc.
 Analog-to-Digital Conversion (ADC) and Digital-to-Analog
Conversion (DAC) are the processes that allow digital computers to
interact with these everyday signals.
 Digital information is different from its continuous counterpart in two
important respects: it is sampled, and it is quantized.
 Both of these restrict how much information a digital signal can
contain.
ADVANTAGES OF DIGITAL TRANSMISSIONS
 Noise immunity
 Error detection and correction
 Ease of multiplexing
 Integration of analog and digital data
 Use of signal regenerators
 Data integrity and security
 Ease of evaluation and measurements
 More suitable for processing
DISADVANTAGES OF DIGITAL TRANSMISSIONS
 More bandwidth requirement
 Need of precise time synchronization
 Additional hardware for encoding/decoding
 Integration of analog and digital data
 Sudden degradation in QoS
 Incompatible with existing analog facilities
ADC
 In electronics, an analog-to-digital converter (ADC, A/D, or A-to-D) is
a system that converts an analog signal, such as a sound picked up by a
microphone or light entering a digital camera, into a digital signal.
 An ADC may also provide an isolated measurement such as an
electronic device that converts an input analog voltage or current to a
digital number representing the magnitude of the voltage or current.
 There are several ADC architectures. Due to the complexity and the
need for precisely matched components, all but the most specialized
ADCs are implemented as integrated circuits (ICs).
ADC
SAMPLING
 The analog signal is continuous in time and it is necessary to convert
this to a flow of digital values.
 It is therefore required to define the rate at which new digital values are
sampled from the analog signal.
 The rate of new values is called the sampling rate or sampling
frequency of the converter.
 A continuously varying band limited signal can be sampled and then
the original signal can be reproduced from the discrete-time values by a
reconstruction filter.
SAMPLING THEOREM
 The Nyquist–Shannon sampling theorem implies that a faithful
reproduction of the original signal is only possible if the sampling rate is
higher than twice the highest frequency of the signal.
 Since a practical ADC cannot make an instantaneous conversion, the input
value must necessarily be held constant during the time that the converter
performs a conversion (called the conversion time).
 An input circuit called a sample and hold performs this task—in most cases
by using a capacitor to store the analog voltage at the input, and using an
electronic switch or gate to disconnect the capacitor from the input.
 Many ADC integrated circuits include the sample and hold subsystem
internally.
SAMPLING THEOREM
 Theorem Statement:
 A continuous time signal can be represented in its samples and can
be recovered back when sampling frequency fs is greater than or
equal to the twice the highest frequency component of message
signal. i. e. fs≥2fm
SAMPLING
SAMPLING
ALIASING
 An ADC works by sampling the value of the input at discrete intervals in
time.
 Provided that the input is sampled above the Nyquist rate, defined as twice
the highest frequency of interest, then all frequencies in the signal can be
reconstructed.
 If frequencies above half the Nyquist rate are sampled, they are incorrectly
detected as lower frequencies, a process referred to as aliasing.
 Aliasing occurs because instantaneously sampling a function at two or
fewer times per cycle results in missed cycles, and therefore the appearance
of an incorrectly lower frequency.
 For example, a 2 kHz sine wave being sampled at 1.5 kHz would be
reconstructed as a 500 Hz sine wave.
AVOIDING ALIASING
 To avoid aliasing, the input to an ADC must be low-pass filtered to remove
frequencies above half the sampling rate.
 This filter is called an anti-aliasing filter, and is essential for a practical
ADC system that is applied to analog signals with higher frequency
content.
 In applications where protection against aliasing is essential, oversampling
may be used to greatly reduce or even eliminate it.
 Although aliasing in most systems is unwanted, it can be exploited to
provide simultaneous down-mixing of a band-limited high-frequency
signal (see undersampling and frequency mixer).
 The alias is effectively the lower heterodyne of the signal frequency and
sampling frequency.
SAMPLING TECHNIQUES
 There are three types of sampling techniques:
 Impulse sampling.
 Natural sampling.
 Flat Top sampling.
SAMPLING TECHNIQUES – IMPULSE SAMPLING
 Impulse sampling can be performed by multiplying input signal x(t) with
impulse train of period 'T'. Here, the amplitude of impulse changes with
respect to amplitude of input signal x(t).
 The output of sampler is given by
SAMPLING TECHNIQUES – NATURAL SAMPLING
 Natural sampling is similar to impulse sampling, except the impulse train is
replaced by pulse train of period T. i.e. multiply input signal x(t) to pulse
train as shown below
SAMPLING TECHNIQUES – FLAT TOP SAMPLING
 During transmission, noise is introduced at top of the transmission pulse
which can be easily removed if the pulse is in the form of flat top. Here, the
top of the samples are flat i.e. they have constant amplitude. Hence, it is
called as flat top sampling or practical sampling. Flat top sampling makes
use of sample and hold circuit.
SAMPLE AND HOLD CIRCUITS
 A Sample and Hold Circuit, sometimes represented as S/H Circuit or S & H Circuit, is
usually used with an Analog to Digital Converter to sample the input analog signal and
hold the sampled signal.
 In the S/H Circuit, the analog signal is sampled for a short interval of time, usually in the
range of 10µS to 1µS.
 After this, the sampled value is hold until the arrival of next input signal to be sampled.
 The duration for holding the sample will be usually between few milliseconds to few
seconds.
 The following image shows a simple block diagram of a typical Sample and Hold Circuit
NEED FOR SAMPLE AND HOLD CIRCUITS
 If the input analog voltage of an ADC changes more than ±1/2 LSB,
then there is a severe chance that the output digital value is an error.
 For the ADC to produce accurate results, the input analog voltage
should be held constant for the duration of the conversion.
 As the name suggests, a S/H Circuit samples the input analog signal
based on a sampling command and holds the output value at its output
until the next sampling command is arrived.
EXPLANATION SAMPLE AND HOLD CIRCUITS
SIMPLE SAMPLE AND HOLD CIRCUITS
 The operating principle of a S/H Circuit with the help of a simplified
circuit diagram of sample and hold circuit consist of two basic
components:
 Analog Switch
 Holding Capacitor
 This circuit tracks the input analog signal until the sample command is
changed to hold command. After the hold command, the capacitor
holds the analog voltage during the analog to digital conversion.
ANALOG SWITCH IN SAMPLE AND HOLD CIRCUITS
 Any FET like JFET or MOSFET can be used as an Analog Switch.
 The Gate-Source voltage VGS is responsible for switching the JFET.
 When VGS is equal to 0V, the JFET acts as a closed switch as it operates in its Ohmic
region.
 When VGS is a large negative voltage (i.e. more negative than VGS(OFF)), the JFET acts as
an open switch as it is cut-off.
 The switch can be either a Shunt Switch or a Series Switch, depending on its position
with respect to input and output.
 The following image shows a JFET configured as both a Shunt Switch and as a Series
Switch.
TYPES OF SAMPLE AND HOLD CIRCUITS
 All the below mentioned circuits use JFET as the switch.
 During the sampling period, the JFET is turned ON and the charging in the holding
capacitor rises to the level of the input analog voltage.
 At the end of the sampling period, the JFET is turned OFF and the holding capacitor
is isolated from the input signal.
 This makes sure that the output voltage is held constant at the value of the input
voltage irrespective of minor changes in the input value.
 To compensate for the low drop-out voltage across the holding capacitor, two
buffers (voltage followers) are used, one at the input and one at the output.
TYPES OF SAMPLE AND HOLD CIRCUITS
 The following image shows an open-loop type S/H Circuit.
 As there is no feedback, this circuit is relatively faster than the coming circuits
(which all are in closed-loop configuration).
 But the feedback in the closed-loop architectures provide higher accuracy figures.
 The acquisition time (discussed in the next section) must be as low as possible.
 It is dependent on three factors:
 The RC time constant, where R is the ON Resistance of the JFET (Ron) and C is the holding
capacitor CH.
 Maximum output current
 Slew-rate of the Op-Amp
TYPES OF SAMPLE AND HOLD CIRCUITS
 A slightly improved circuit than the first one is presented in the next circuit. In this
configuration, the ON Resistance of the JFET is brought into the feedback loop and
hence, the acquisition time is dependent on the other two factors.
TYPES OF SAMPLE AND HOLD CIRCUITS
 The next circuit is further improved when compared to the previous circuit by
providing voltage gain. The voltage gain of the circuit can be calculated using
the input resistor R1 and the feedback resistor RF as follows:
A = 1 + (RF / R1)
TYPES OF SAMPLE AND HOLD CIRCUITS
 The final circuit offers additional advantages than the previous circuit.
 The important one is that the position of the holding capacitor is changed and
as a result, the voltage at non-inverting terminal of A2 is equal to the voltage
across the capacitor divided by the open-loop gain of A2.
 This ensure a faster charging time of the holding capacitor and subsequently a
shorter acquisition time.
PERFORMANCE PARAMETERS OF S&H CIRCUITS
 The performance of an S/H Circuit can be characterized by parameters
that are commonly used for an amplifier like Input Offset Voltage, Gain
Error, Non-linearity and so on.
 But there are a few characteristics that are specific to the S/H Circuits.
 These characteristics are helpful in analyzing its performance during
the transition from sampling mode to hold mode (and vice versa) and
also during hold mode operations.
PERFORMANCE PARAMETERS OF S&H CIRCUITS
Acquisition Time (tac):
 The time required for the charge in the holding capacitor to rise up to a
level that is close to the input voltage during the sampling is called
acquisition time. It is affected by three factors:
 The RC Time Constant
 The Slew-Rate of the Op-Amp
 The maximum output current of the Op-Amp
PERFORMANCE PARAMETERS OF S&H CIRCUITS
Aperture Time (tap)
 The time delay between the initiation of VO tracking the Vi and the
initiation of the hold command is called the Aperture Time. This delay
is usually due to the propagation delays through the driver and the
switch circuits.
 For a precise timing operation, the hold command must be initiated in
advance by an amount of aperture time.
Aperture Uncertainty (∆ tap)
 The Aperture time will not be the same for all the sample and will vary
from sample to sample. This uncertainty is called Aperture Uncertainty.
This will severely affect the advancing of the hold command.
PERFORMANCE PARAMETERS OF S&H CIRCUITS
Hold Mode Settling Time (ts)
 The hold mode settling time is the time taken by the output VO to settle within
the specified error band (usually 1%, 0.1% or 0.01%) after the application of
hold command.
Hold Step
 During the switching from sample mode to hold mode, there might an
unwanted transfer of charge between the switch and the holding capacitor
(mainly due to the parasitic capacitances). This will affect the capacitor voltage
as well as the output voltage. This change in the output voltage from the
desired voltage is called Hold Step.
PERFORMANCE PARAMETERS OF S&H CIRCUITS
Feedthrough
 Again, the parasitic capacitances in the switch may cause AC coupling between
VO and Vi in hold mode. As a result, the output voltage may vary with changes
in the input voltage and this is referred to as feedthrough.
Droop
 Voltage Droop is a phenomenon where the voltage across the holding capacitor
drops down due to leakage currents.
ADVANTAGES OF S&H CIRCUITS
Advantages of Sample and Hold Circuit
 The main and important advantage of a typical SH Circuit is to aid an
Analog to Digital Conversion process by holding the sampled analog
input voltage.
 In multichannel ADCs, where synchronization between different
channels is important, an SH circuit can help by sampling analog
signals from all the channels at the same time.
 In multiplexed circuits, the crosstalk can be reduced with an SH circuit.
APPLICATIONS OF S&H CIRCUITS
Applications of Sample and Hold Circuit
 Some of the important applications are mentioned below:
 Analog to Digital Converter Circuits (ADC)
 Digital Interface Circuits
 Operational Amplifiers
 Analog De-multiplexers
 Data distribution systems
 Storage of outputs of multiplexers
 Pulse Modulation Systems
QUANTIZATION
 Quantization, in mathematics and digital signal processing, is the
process of mapping input values from a large set (often a continuous
set) to output values in a (countable) smaller set, often with a finite
number of elements.
 Rounding and truncation are typical examples of quantization
processes.
 Quantization is involved to some degree in nearly all digital signal
processing, as the process of representing a signal in digital form
ordinarily involves rounding.
 Quantization also forms the core of essentially all lossy compression
algorithms.
QUANTIZATION – EXPLANATION
 The simplest way to quantize a signal is to choose the digital amplitude value
closest to the original analog amplitude.
 This example shows the original analog signal (green), the quantized signal
(black dots), the signal reconstructed from the quantized signal (yellow) and
the difference between the original signal and the reconstructed signal (red).
 The difference between the original signal and the reconstructed signal is the
quantization error and, in this simple quantization scheme, is a deterministic
function of the input signal.
PROCESS
 The following figure represents an analog signal.
 This signal to get converted into digital, has to undergo sampling and
quantizing.
 The quantizing of an analog signal is done by discretizing the signal
with a number of quantization levels. Quantization is representing the
sampled values of the amplitude by a finite set of levels, which means
converting a continuous-amplitude sample into a discrete-time signal.
PROCESS
 The following figure shows how an analog signal gets quantized. The
blue line represents analog signal while the brown one represents the
quantized signal.
 Both sampling and quantization result in the loss of information. The
quality of a Quantizer output depends upon the number of quantization
levels used.
PROCESS
 The discrete amplitudes of the quantized output are called as
representation levels or reconstruction levels. The spacing between the
two adjacent representation levels is called a quantum or step-size.
 The following figure shows the resultant quantized signal which is the
digital form for the given analog signal.
 This is also called as Stair-case waveform, in accordance with its
shape.
TYPES OF QUANTIZATION
 There are two types of Quantization - Uniform Quantization and Non-
uniform Quantization.
 The type of quantization in which the quantization levels are uniformly
spaced is termed as a Uniform Quantization.
 The type of quantization in which the quantization levels are unequal
and mostly the relation between them is logarithmic, is termed as a
Non-uniform Quantization.
UNIFORM QUANTIZATION
 There are two types of uniform quantization. They are Mid-Rise type
and Mid-Tread type.
 The following figures represent the two types of uniform quantization
 Figure 1 shows the mid-rise type and figure 2 shows the mid-tread type
of uniform quantization.
QUANTIZATION ERROR
 For any system, during its functioning, there is always a difference in
the values of its input and output.
 The processing of the system results in an error, which is the difference
of those values.
 The difference between an input value and its quantized value is called
a Quantization Error.
 A Quantizer is a logarithmic function that performs Quantization
rounding off the value.
 An analog-to-digital converter (ADC) works as a quantizer.
QUANTIZATION ERROR
 The following figure illustrates an example for a quantization error,
indicating the difference between the original signal and the quantized
signal.
QUANTIZATION NOISE
 It is a type of quantization error, which usually occurs in analog audio
signal, while quantizing it to digital.
 For example, in music, the signals keep changing continuously, where
regularity is not found in errors.
 Such errors create a wideband noise called as Quantization Noise

More Related Content

What's hot

Application of DSP
Application of DSPApplication of DSP
Application of DSPKUNAL RANA
 
Pulse Modulation ppt
Pulse Modulation pptPulse Modulation ppt
Pulse Modulation pptsanjeev2419
 
Instrumentation amplifier
Instrumentation amplifierInstrumentation amplifier
Instrumentation amplifiermohdabuzar5
 
NYQUIST CRITERION FOR ZERO ISI
NYQUIST CRITERION FOR ZERO ISINYQUIST CRITERION FOR ZERO ISI
NYQUIST CRITERION FOR ZERO ISIFAIZAN SHAFI
 
Lag lead compensator design in frequency domain 7th lecture
Lag lead compensator design in frequency domain  7th lectureLag lead compensator design in frequency domain  7th lecture
Lag lead compensator design in frequency domain 7th lectureKhalaf Gaeid Alshammery
 
discrete time signals and systems
 discrete time signals and systems  discrete time signals and systems
discrete time signals and systems Zlatan Ahmadovic
 
noise in pcm | Communication Systems
noise in pcm | Communication Systemsnoise in pcm | Communication Systems
noise in pcm | Communication SystemsLearn By Watch
 
Pulse amplitude modulation
Pulse amplitude modulationPulse amplitude modulation
Pulse amplitude modulationabi sivaraj
 
M ary psk modulation
M ary psk modulationM ary psk modulation
M ary psk modulationAhmed Diaa
 
Differential amplifier
Differential amplifierDifferential amplifier
Differential amplifiersarunkutti
 

What's hot (20)

Telemetry
TelemetryTelemetry
Telemetry
 
Application of DSP
Application of DSPApplication of DSP
Application of DSP
 
Multirate DSP
Multirate DSPMultirate DSP
Multirate DSP
 
Pulse Modulation ppt
Pulse Modulation pptPulse Modulation ppt
Pulse Modulation ppt
 
PAM
PAMPAM
PAM
 
Analog to digital converters, adc
Analog to digital converters, adcAnalog to digital converters, adc
Analog to digital converters, adc
 
Sample and hold circuit
Sample and hold circuitSample and hold circuit
Sample and hold circuit
 
Instrumentation amplifier
Instrumentation amplifierInstrumentation amplifier
Instrumentation amplifier
 
Adaptive equalization
Adaptive equalizationAdaptive equalization
Adaptive equalization
 
NYQUIST CRITERION FOR ZERO ISI
NYQUIST CRITERION FOR ZERO ISINYQUIST CRITERION FOR ZERO ISI
NYQUIST CRITERION FOR ZERO ISI
 
Frequency translation
Frequency translationFrequency translation
Frequency translation
 
Lag lead compensator design in frequency domain 7th lecture
Lag lead compensator design in frequency domain  7th lectureLag lead compensator design in frequency domain  7th lecture
Lag lead compensator design in frequency domain 7th lecture
 
OPERATIONS ON SIGNALS
OPERATIONS ON SIGNALSOPERATIONS ON SIGNALS
OPERATIONS ON SIGNALS
 
Sampling theorem
Sampling theoremSampling theorem
Sampling theorem
 
discrete time signals and systems
 discrete time signals and systems  discrete time signals and systems
discrete time signals and systems
 
Ditial to Analog Converter
Ditial to Analog ConverterDitial to Analog Converter
Ditial to Analog Converter
 
noise in pcm | Communication Systems
noise in pcm | Communication Systemsnoise in pcm | Communication Systems
noise in pcm | Communication Systems
 
Pulse amplitude modulation
Pulse amplitude modulationPulse amplitude modulation
Pulse amplitude modulation
 
M ary psk modulation
M ary psk modulationM ary psk modulation
M ary psk modulation
 
Differential amplifier
Differential amplifierDifferential amplifier
Differential amplifier
 

Similar to ADC An Introduction

Project_Kaveh & Mohammad
Project_Kaveh & MohammadProject_Kaveh & Mohammad
Project_Kaveh & MohammadKaveh Dehno
 
Design of Ota-C Filter for Biomedical Applications
Design of Ota-C Filter for Biomedical ApplicationsDesign of Ota-C Filter for Biomedical Applications
Design of Ota-C Filter for Biomedical ApplicationsIOSR Journals
 
High Speed and Low Pedestal Error Bootstrapped CMOS Sample and Hold Circuit
High Speed and Low Pedestal Error Bootstrapped CMOS Sample and Hold CircuitHigh Speed and Low Pedestal Error Bootstrapped CMOS Sample and Hold Circuit
High Speed and Low Pedestal Error Bootstrapped CMOS Sample and Hold CircuitIJECEIAES
 
A new precision peak detector full wave rectifier
A new precision peak detector full wave rectifierA new precision peak detector full wave rectifier
A new precision peak detector full wave rectifierVishal kakade
 
Analog & Digital Integrated Circuits - Material (Short Answers)
Analog & Digital Integrated Circuits -  Material (Short Answers) Analog & Digital Integrated Circuits -  Material (Short Answers)
Analog & Digital Integrated Circuits - Material (Short Answers) Mathankumar S
 
MODULE-2_SIGNAL_CONDITIONING.pptx
MODULE-2_SIGNAL_CONDITIONING.pptxMODULE-2_SIGNAL_CONDITIONING.pptx
MODULE-2_SIGNAL_CONDITIONING.pptxManjunathtv2
 
642135IJSETR12691-1615
642135IJSETR12691-1615642135IJSETR12691-1615
642135IJSETR12691-1615Gaini Laxman
 
Design of an ADC using High Precision Comparator with Time Domain Offset Canc...
Design of an ADC using High Precision Comparator with Time Domain Offset Canc...Design of an ADC using High Precision Comparator with Time Domain Offset Canc...
Design of an ADC using High Precision Comparator with Time Domain Offset Canc...IJTET Journal
 
Force Sensor Data Acquisition
Force Sensor Data AcquisitionForce Sensor Data Acquisition
Force Sensor Data AcquisitionTacuna Systems
 
IRJET- A Comparative Analysis of CMOS Amplifiers for ECG Signals
IRJET- A Comparative Analysis of CMOS Amplifiers for ECG SignalsIRJET- A Comparative Analysis of CMOS Amplifiers for ECG Signals
IRJET- A Comparative Analysis of CMOS Amplifiers for ECG SignalsIRJET Journal
 
Kevin Glass Doctoral Qualifying Exam
Kevin Glass Doctoral Qualifying ExamKevin Glass Doctoral Qualifying Exam
Kevin Glass Doctoral Qualifying ExamKevin Glass
 
Kevin Glass Doctoral Qualifying Exam
Kevin Glass Doctoral Qualifying ExamKevin Glass Doctoral Qualifying Exam
Kevin Glass Doctoral Qualifying ExamKevin Glass
 
Design of Low Power & High Speed Comparator with 0.18μm Technology for ADC Ap...
Design of Low Power & High Speed Comparator with 0.18μm Technology for ADC Ap...Design of Low Power & High Speed Comparator with 0.18μm Technology for ADC Ap...
Design of Low Power & High Speed Comparator with 0.18μm Technology for ADC Ap...IJERA Editor
 
Digial instrumentation fnal
Digial instrumentation fnalDigial instrumentation fnal
Digial instrumentation fnalBishal Rimal
 
Communication engineering notes uniit ii
Communication engineering notes uniit iiCommunication engineering notes uniit ii
Communication engineering notes uniit iiManoj Kumar
 
Fuzzy Logic Controller Based High Frequency Link AC-AC Converter For Voltage ...
Fuzzy Logic Controller Based High Frequency Link AC-AC Converter For Voltage ...Fuzzy Logic Controller Based High Frequency Link AC-AC Converter For Voltage ...
Fuzzy Logic Controller Based High Frequency Link AC-AC Converter For Voltage ...IJTET Journal
 

Similar to ADC An Introduction (20)

Project_Kaveh & Mohammad
Project_Kaveh & MohammadProject_Kaveh & Mohammad
Project_Kaveh & Mohammad
 
Design of Ota-C Filter for Biomedical Applications
Design of Ota-C Filter for Biomedical ApplicationsDesign of Ota-C Filter for Biomedical Applications
Design of Ota-C Filter for Biomedical Applications
 
High Speed and Low Pedestal Error Bootstrapped CMOS Sample and Hold Circuit
High Speed and Low Pedestal Error Bootstrapped CMOS Sample and Hold CircuitHigh Speed and Low Pedestal Error Bootstrapped CMOS Sample and Hold Circuit
High Speed and Low Pedestal Error Bootstrapped CMOS Sample and Hold Circuit
 
A new precision peak detector full wave rectifier
A new precision peak detector full wave rectifierA new precision peak detector full wave rectifier
A new precision peak detector full wave rectifier
 
Analog & Digital Integrated Circuits - Material (Short Answers)
Analog & Digital Integrated Circuits -  Material (Short Answers) Analog & Digital Integrated Circuits -  Material (Short Answers)
Analog & Digital Integrated Circuits - Material (Short Answers)
 
MODULE-2_SIGNAL_CONDITIONING.pptx
MODULE-2_SIGNAL_CONDITIONING.pptxMODULE-2_SIGNAL_CONDITIONING.pptx
MODULE-2_SIGNAL_CONDITIONING.pptx
 
642135IJSETR12691-1615
642135IJSETR12691-1615642135IJSETR12691-1615
642135IJSETR12691-1615
 
Design of an ADC using High Precision Comparator with Time Domain Offset Canc...
Design of an ADC using High Precision Comparator with Time Domain Offset Canc...Design of an ADC using High Precision Comparator with Time Domain Offset Canc...
Design of an ADC using High Precision Comparator with Time Domain Offset Canc...
 
Force Sensor Data Acquisition
Force Sensor Data AcquisitionForce Sensor Data Acquisition
Force Sensor Data Acquisition
 
En34855860
En34855860En34855860
En34855860
 
IRJET- A Comparative Analysis of CMOS Amplifiers for ECG Signals
IRJET- A Comparative Analysis of CMOS Amplifiers for ECG SignalsIRJET- A Comparative Analysis of CMOS Amplifiers for ECG Signals
IRJET- A Comparative Analysis of CMOS Amplifiers for ECG Signals
 
Qualprez
QualprezQualprez
Qualprez
 
Kevin Glass Doctoral Qualifying Exam
Kevin Glass Doctoral Qualifying ExamKevin Glass Doctoral Qualifying Exam
Kevin Glass Doctoral Qualifying Exam
 
Kevin Glass Doctoral Qualifying Exam
Kevin Glass Doctoral Qualifying ExamKevin Glass Doctoral Qualifying Exam
Kevin Glass Doctoral Qualifying Exam
 
Design of Low Power & High Speed Comparator with 0.18μm Technology for ADC Ap...
Design of Low Power & High Speed Comparator with 0.18μm Technology for ADC Ap...Design of Low Power & High Speed Comparator with 0.18μm Technology for ADC Ap...
Design of Low Power & High Speed Comparator with 0.18μm Technology for ADC Ap...
 
Digial instrumentation fnal
Digial instrumentation fnalDigial instrumentation fnal
Digial instrumentation fnal
 
Communication engineering notes uniit ii
Communication engineering notes uniit iiCommunication engineering notes uniit ii
Communication engineering notes uniit ii
 
Signal conditioning
Signal conditioningSignal conditioning
Signal conditioning
 
Basics of amplifier
Basics of amplifierBasics of amplifier
Basics of amplifier
 
Fuzzy Logic Controller Based High Frequency Link AC-AC Converter For Voltage ...
Fuzzy Logic Controller Based High Frequency Link AC-AC Converter For Voltage ...Fuzzy Logic Controller Based High Frequency Link AC-AC Converter For Voltage ...
Fuzzy Logic Controller Based High Frequency Link AC-AC Converter For Voltage ...
 

More from National Engineering College

Classification of Systems - Additional Solved Problems
Classification of Systems - Additional Solved ProblemsClassification of Systems - Additional Solved Problems
Classification of Systems - Additional Solved ProblemsNational Engineering College
 
Classification of Systems - Procedural steps to solve problems
Classification of Systems - Procedural steps to solve problemsClassification of Systems - Procedural steps to solve problems
Classification of Systems - Procedural steps to solve problemsNational Engineering College
 
Basic operation on Signals - Independent Variables |Problem solving technique|
Basic operation on Signals - Independent Variables |Problem solving technique|Basic operation on Signals - Independent Variables |Problem solving technique|
Basic operation on Signals - Independent Variables |Problem solving technique|National Engineering College
 

More from National Engineering College (20)

ADC - Types (Analog to Digital Converter)
ADC - Types (Analog to Digital Converter)ADC - Types (Analog to Digital Converter)
ADC - Types (Analog to Digital Converter)
 
LTI system causality and stability
LTI system   causality and stabilityLTI system   causality and stability
LTI system causality and stability
 
Arbitrary representation of sequence
Arbitrary representation of sequenceArbitrary representation of sequence
Arbitrary representation of sequence
 
Classification of Systems - Additional Solved Problems
Classification of Systems - Additional Solved ProblemsClassification of Systems - Additional Solved Problems
Classification of Systems - Additional Solved Problems
 
Stable & Unstable Systems |Solved problems|
Stable & Unstable Systems |Solved problems|Stable & Unstable Systems |Solved problems|
Stable & Unstable Systems |Solved problems|
 
Linear & Non-Linear Systems |Solved problems|
Linear & Non-Linear Systems |Solved problems|Linear & Non-Linear Systems |Solved problems|
Linear & Non-Linear Systems |Solved problems|
 
Causal & Non-Causal Systems |Solved problems|
Causal & Non-Causal Systems |Solved problems|Causal & Non-Causal Systems |Solved problems|
Causal & Non-Causal Systems |Solved problems|
 
Static & Dynamic Systems |Solved problems|
Static & Dynamic Systems |Solved problems|Static & Dynamic Systems |Solved problems|
Static & Dynamic Systems |Solved problems|
 
Classification of Systems - Procedural steps to solve problems
Classification of Systems - Procedural steps to solve problemsClassification of Systems - Procedural steps to solve problems
Classification of Systems - Procedural steps to solve problems
 
Discrete Time Systems & its classifications
Discrete Time Systems & its classificationsDiscrete Time Systems & its classifications
Discrete Time Systems & its classifications
 
Even & Odd Signals |Solved Problems|
Even & Odd Signals |Solved Problems|Even & Odd Signals |Solved Problems|
Even & Odd Signals |Solved Problems|
 
Energy & Power Signals |Solved Problems|
Energy & Power Signals |Solved Problems|Energy & Power Signals |Solved Problems|
Energy & Power Signals |Solved Problems|
 
Basic operation on Signals - Independent Variables |Problem solving technique|
Basic operation on Signals - Independent Variables |Problem solving technique|Basic operation on Signals - Independent Variables |Problem solving technique|
Basic operation on Signals - Independent Variables |Problem solving technique|
 
Operation on signals - Independent variables
Operation on signals - Independent variablesOperation on signals - Independent variables
Operation on signals - Independent variables
 
Operation on signals - Dependent variables
Operation on signals - Dependent variablesOperation on signals - Dependent variables
Operation on signals - Dependent variables
 
Elementary signals
Elementary signalsElementary signals
Elementary signals
 
Representation of discrete time signals
Representation of discrete time signalsRepresentation of discrete time signals
Representation of discrete time signals
 
Classification of Digital signals
Classification of Digital signalsClassification of Digital signals
Classification of Digital signals
 
Signals and Systems
Signals and SystemsSignals and Systems
Signals and Systems
 
Introduction to digital signal processor
Introduction to digital signal processorIntroduction to digital signal processor
Introduction to digital signal processor
 

Recently uploaded

Internship report on mechanical engineering
Internship report on mechanical engineeringInternship report on mechanical engineering
Internship report on mechanical engineeringmalavadedarshan25
 
Current Transformer Drawing and GTP for MSETCL
Current Transformer Drawing and GTP for MSETCLCurrent Transformer Drawing and GTP for MSETCL
Current Transformer Drawing and GTP for MSETCLDeelipZope
 
Application of Residue Theorem to evaluate real integrations.pptx
Application of Residue Theorem to evaluate real integrations.pptxApplication of Residue Theorem to evaluate real integrations.pptx
Application of Residue Theorem to evaluate real integrations.pptx959SahilShah
 
Heart Disease Prediction using machine learning.pptx
Heart Disease Prediction using machine learning.pptxHeart Disease Prediction using machine learning.pptx
Heart Disease Prediction using machine learning.pptxPoojaBan
 
Oxy acetylene welding presentation note.
Oxy acetylene welding presentation note.Oxy acetylene welding presentation note.
Oxy acetylene welding presentation note.eptoze12
 
IVE Industry Focused Event - Defence Sector 2024
IVE Industry Focused Event - Defence Sector 2024IVE Industry Focused Event - Defence Sector 2024
IVE Industry Focused Event - Defence Sector 2024Mark Billinghurst
 
CCS355 Neural Network & Deep Learning Unit II Notes with Question bank .pdf
CCS355 Neural Network & Deep Learning Unit II Notes with Question bank .pdfCCS355 Neural Network & Deep Learning Unit II Notes with Question bank .pdf
CCS355 Neural Network & Deep Learning Unit II Notes with Question bank .pdfAsst.prof M.Gokilavani
 
CCS355 Neural Network & Deep Learning UNIT III notes and Question bank .pdf
CCS355 Neural Network & Deep Learning UNIT III notes and Question bank .pdfCCS355 Neural Network & Deep Learning UNIT III notes and Question bank .pdf
CCS355 Neural Network & Deep Learning UNIT III notes and Question bank .pdfAsst.prof M.Gokilavani
 
VIP Call Girls Service Hitech City Hyderabad Call +91-8250192130
VIP Call Girls Service Hitech City Hyderabad Call +91-8250192130VIP Call Girls Service Hitech City Hyderabad Call +91-8250192130
VIP Call Girls Service Hitech City Hyderabad Call +91-8250192130Suhani Kapoor
 
Artificial-Intelligence-in-Electronics (K).pptx
Artificial-Intelligence-in-Electronics (K).pptxArtificial-Intelligence-in-Electronics (K).pptx
Artificial-Intelligence-in-Electronics (K).pptxbritheesh05
 
HARMONY IN THE NATURE AND EXISTENCE - Unit-IV
HARMONY IN THE NATURE AND EXISTENCE - Unit-IVHARMONY IN THE NATURE AND EXISTENCE - Unit-IV
HARMONY IN THE NATURE AND EXISTENCE - Unit-IVRajaP95
 
HARMONY IN THE HUMAN BEING - Unit-II UHV-2
HARMONY IN THE HUMAN BEING - Unit-II UHV-2HARMONY IN THE HUMAN BEING - Unit-II UHV-2
HARMONY IN THE HUMAN BEING - Unit-II UHV-2RajaP95
 
Gfe Mayur Vihar Call Girls Service WhatsApp -> 9999965857 Available 24x7 ^ De...
Gfe Mayur Vihar Call Girls Service WhatsApp -> 9999965857 Available 24x7 ^ De...Gfe Mayur Vihar Call Girls Service WhatsApp -> 9999965857 Available 24x7 ^ De...
Gfe Mayur Vihar Call Girls Service WhatsApp -> 9999965857 Available 24x7 ^ De...srsj9000
 
chaitra-1.pptx fake news detection using machine learning
chaitra-1.pptx  fake news detection using machine learningchaitra-1.pptx  fake news detection using machine learning
chaitra-1.pptx fake news detection using machine learningmisbanausheenparvam
 
OSVC_Meta-Data based Simulation Automation to overcome Verification Challenge...
OSVC_Meta-Data based Simulation Automation to overcome Verification Challenge...OSVC_Meta-Data based Simulation Automation to overcome Verification Challenge...
OSVC_Meta-Data based Simulation Automation to overcome Verification Challenge...Soham Mondal
 
What are the advantages and disadvantages of membrane structures.pptx
What are the advantages and disadvantages of membrane structures.pptxWhat are the advantages and disadvantages of membrane structures.pptx
What are the advantages and disadvantages of membrane structures.pptxwendy cai
 
Architect Hassan Khalil Portfolio for 2024
Architect Hassan Khalil Portfolio for 2024Architect Hassan Khalil Portfolio for 2024
Architect Hassan Khalil Portfolio for 2024hassan khalil
 
Sachpazis Costas: Geotechnical Engineering: A student's Perspective Introduction
Sachpazis Costas: Geotechnical Engineering: A student's Perspective IntroductionSachpazis Costas: Geotechnical Engineering: A student's Perspective Introduction
Sachpazis Costas: Geotechnical Engineering: A student's Perspective IntroductionDr.Costas Sachpazis
 

Recently uploaded (20)

Internship report on mechanical engineering
Internship report on mechanical engineeringInternship report on mechanical engineering
Internship report on mechanical engineering
 
POWER SYSTEMS-1 Complete notes examples
POWER SYSTEMS-1 Complete notes  examplesPOWER SYSTEMS-1 Complete notes  examples
POWER SYSTEMS-1 Complete notes examples
 
young call girls in Rajiv Chowk🔝 9953056974 🔝 Delhi escort Service
young call girls in Rajiv Chowk🔝 9953056974 🔝 Delhi escort Serviceyoung call girls in Rajiv Chowk🔝 9953056974 🔝 Delhi escort Service
young call girls in Rajiv Chowk🔝 9953056974 🔝 Delhi escort Service
 
Current Transformer Drawing and GTP for MSETCL
Current Transformer Drawing and GTP for MSETCLCurrent Transformer Drawing and GTP for MSETCL
Current Transformer Drawing and GTP for MSETCL
 
Application of Residue Theorem to evaluate real integrations.pptx
Application of Residue Theorem to evaluate real integrations.pptxApplication of Residue Theorem to evaluate real integrations.pptx
Application of Residue Theorem to evaluate real integrations.pptx
 
Heart Disease Prediction using machine learning.pptx
Heart Disease Prediction using machine learning.pptxHeart Disease Prediction using machine learning.pptx
Heart Disease Prediction using machine learning.pptx
 
Oxy acetylene welding presentation note.
Oxy acetylene welding presentation note.Oxy acetylene welding presentation note.
Oxy acetylene welding presentation note.
 
IVE Industry Focused Event - Defence Sector 2024
IVE Industry Focused Event - Defence Sector 2024IVE Industry Focused Event - Defence Sector 2024
IVE Industry Focused Event - Defence Sector 2024
 
CCS355 Neural Network & Deep Learning Unit II Notes with Question bank .pdf
CCS355 Neural Network & Deep Learning Unit II Notes with Question bank .pdfCCS355 Neural Network & Deep Learning Unit II Notes with Question bank .pdf
CCS355 Neural Network & Deep Learning Unit II Notes with Question bank .pdf
 
CCS355 Neural Network & Deep Learning UNIT III notes and Question bank .pdf
CCS355 Neural Network & Deep Learning UNIT III notes and Question bank .pdfCCS355 Neural Network & Deep Learning UNIT III notes and Question bank .pdf
CCS355 Neural Network & Deep Learning UNIT III notes and Question bank .pdf
 
VIP Call Girls Service Hitech City Hyderabad Call +91-8250192130
VIP Call Girls Service Hitech City Hyderabad Call +91-8250192130VIP Call Girls Service Hitech City Hyderabad Call +91-8250192130
VIP Call Girls Service Hitech City Hyderabad Call +91-8250192130
 
Artificial-Intelligence-in-Electronics (K).pptx
Artificial-Intelligence-in-Electronics (K).pptxArtificial-Intelligence-in-Electronics (K).pptx
Artificial-Intelligence-in-Electronics (K).pptx
 
HARMONY IN THE NATURE AND EXISTENCE - Unit-IV
HARMONY IN THE NATURE AND EXISTENCE - Unit-IVHARMONY IN THE NATURE AND EXISTENCE - Unit-IV
HARMONY IN THE NATURE AND EXISTENCE - Unit-IV
 
HARMONY IN THE HUMAN BEING - Unit-II UHV-2
HARMONY IN THE HUMAN BEING - Unit-II UHV-2HARMONY IN THE HUMAN BEING - Unit-II UHV-2
HARMONY IN THE HUMAN BEING - Unit-II UHV-2
 
Gfe Mayur Vihar Call Girls Service WhatsApp -> 9999965857 Available 24x7 ^ De...
Gfe Mayur Vihar Call Girls Service WhatsApp -> 9999965857 Available 24x7 ^ De...Gfe Mayur Vihar Call Girls Service WhatsApp -> 9999965857 Available 24x7 ^ De...
Gfe Mayur Vihar Call Girls Service WhatsApp -> 9999965857 Available 24x7 ^ De...
 
chaitra-1.pptx fake news detection using machine learning
chaitra-1.pptx  fake news detection using machine learningchaitra-1.pptx  fake news detection using machine learning
chaitra-1.pptx fake news detection using machine learning
 
OSVC_Meta-Data based Simulation Automation to overcome Verification Challenge...
OSVC_Meta-Data based Simulation Automation to overcome Verification Challenge...OSVC_Meta-Data based Simulation Automation to overcome Verification Challenge...
OSVC_Meta-Data based Simulation Automation to overcome Verification Challenge...
 
What are the advantages and disadvantages of membrane structures.pptx
What are the advantages and disadvantages of membrane structures.pptxWhat are the advantages and disadvantages of membrane structures.pptx
What are the advantages and disadvantages of membrane structures.pptx
 
Architect Hassan Khalil Portfolio for 2024
Architect Hassan Khalil Portfolio for 2024Architect Hassan Khalil Portfolio for 2024
Architect Hassan Khalil Portfolio for 2024
 
Sachpazis Costas: Geotechnical Engineering: A student's Perspective Introduction
Sachpazis Costas: Geotechnical Engineering: A student's Perspective IntroductionSachpazis Costas: Geotechnical Engineering: A student's Perspective Introduction
Sachpazis Costas: Geotechnical Engineering: A student's Perspective Introduction
 

ADC An Introduction

  • 1. 15EE55C – DIGITAL SIGNAL PROCESSING AND ITS APPLICATIONS INTRODUCTION Dr. M. Bakrutheen AP(SG)/EEE Mr. K. Karthik Kumar AP/EEE DEPARTMENT OF ELECTRICAL AND ELECTRONICS ENGINEERING NATIONAL ENGINEERING COLLEGE, K.R. NAGAR, KOVILPATTI – 628 503 (An Autonomous Institution, Affiliated to Anna University – Chennai)
  • 2. INTRODUCTION  Most of the signals directly encountered in science and engineering are continuous: light intensity that changes with distance; voltage that varies over time; a chemical reaction rate that depends on temperature, etc.  Analog-to-Digital Conversion (ADC) and Digital-to-Analog Conversion (DAC) are the processes that allow digital computers to interact with these everyday signals.  Digital information is different from its continuous counterpart in two important respects: it is sampled, and it is quantized.  Both of these restrict how much information a digital signal can contain.
  • 3. ADVANTAGES OF DIGITAL TRANSMISSIONS  Noise immunity  Error detection and correction  Ease of multiplexing  Integration of analog and digital data  Use of signal regenerators  Data integrity and security  Ease of evaluation and measurements  More suitable for processing
  • 4. DISADVANTAGES OF DIGITAL TRANSMISSIONS  More bandwidth requirement  Need of precise time synchronization  Additional hardware for encoding/decoding  Integration of analog and digital data  Sudden degradation in QoS  Incompatible with existing analog facilities
  • 5. ADC  In electronics, an analog-to-digital converter (ADC, A/D, or A-to-D) is a system that converts an analog signal, such as a sound picked up by a microphone or light entering a digital camera, into a digital signal.  An ADC may also provide an isolated measurement such as an electronic device that converts an input analog voltage or current to a digital number representing the magnitude of the voltage or current.  There are several ADC architectures. Due to the complexity and the need for precisely matched components, all but the most specialized ADCs are implemented as integrated circuits (ICs).
  • 6. ADC
  • 7. SAMPLING  The analog signal is continuous in time and it is necessary to convert this to a flow of digital values.  It is therefore required to define the rate at which new digital values are sampled from the analog signal.  The rate of new values is called the sampling rate or sampling frequency of the converter.  A continuously varying band limited signal can be sampled and then the original signal can be reproduced from the discrete-time values by a reconstruction filter.
  • 8. SAMPLING THEOREM  The Nyquist–Shannon sampling theorem implies that a faithful reproduction of the original signal is only possible if the sampling rate is higher than twice the highest frequency of the signal.  Since a practical ADC cannot make an instantaneous conversion, the input value must necessarily be held constant during the time that the converter performs a conversion (called the conversion time).  An input circuit called a sample and hold performs this task—in most cases by using a capacitor to store the analog voltage at the input, and using an electronic switch or gate to disconnect the capacitor from the input.  Many ADC integrated circuits include the sample and hold subsystem internally.
  • 9. SAMPLING THEOREM  Theorem Statement:  A continuous time signal can be represented in its samples and can be recovered back when sampling frequency fs is greater than or equal to the twice the highest frequency component of message signal. i. e. fs≥2fm
  • 12. ALIASING  An ADC works by sampling the value of the input at discrete intervals in time.  Provided that the input is sampled above the Nyquist rate, defined as twice the highest frequency of interest, then all frequencies in the signal can be reconstructed.  If frequencies above half the Nyquist rate are sampled, they are incorrectly detected as lower frequencies, a process referred to as aliasing.  Aliasing occurs because instantaneously sampling a function at two or fewer times per cycle results in missed cycles, and therefore the appearance of an incorrectly lower frequency.  For example, a 2 kHz sine wave being sampled at 1.5 kHz would be reconstructed as a 500 Hz sine wave.
  • 13. AVOIDING ALIASING  To avoid aliasing, the input to an ADC must be low-pass filtered to remove frequencies above half the sampling rate.  This filter is called an anti-aliasing filter, and is essential for a practical ADC system that is applied to analog signals with higher frequency content.  In applications where protection against aliasing is essential, oversampling may be used to greatly reduce or even eliminate it.  Although aliasing in most systems is unwanted, it can be exploited to provide simultaneous down-mixing of a band-limited high-frequency signal (see undersampling and frequency mixer).  The alias is effectively the lower heterodyne of the signal frequency and sampling frequency.
  • 14. SAMPLING TECHNIQUES  There are three types of sampling techniques:  Impulse sampling.  Natural sampling.  Flat Top sampling.
  • 15. SAMPLING TECHNIQUES – IMPULSE SAMPLING  Impulse sampling can be performed by multiplying input signal x(t) with impulse train of period 'T'. Here, the amplitude of impulse changes with respect to amplitude of input signal x(t).  The output of sampler is given by
  • 16. SAMPLING TECHNIQUES – NATURAL SAMPLING  Natural sampling is similar to impulse sampling, except the impulse train is replaced by pulse train of period T. i.e. multiply input signal x(t) to pulse train as shown below
  • 17. SAMPLING TECHNIQUES – FLAT TOP SAMPLING  During transmission, noise is introduced at top of the transmission pulse which can be easily removed if the pulse is in the form of flat top. Here, the top of the samples are flat i.e. they have constant amplitude. Hence, it is called as flat top sampling or practical sampling. Flat top sampling makes use of sample and hold circuit.
  • 18. SAMPLE AND HOLD CIRCUITS  A Sample and Hold Circuit, sometimes represented as S/H Circuit or S & H Circuit, is usually used with an Analog to Digital Converter to sample the input analog signal and hold the sampled signal.  In the S/H Circuit, the analog signal is sampled for a short interval of time, usually in the range of 10µS to 1µS.  After this, the sampled value is hold until the arrival of next input signal to be sampled.  The duration for holding the sample will be usually between few milliseconds to few seconds.  The following image shows a simple block diagram of a typical Sample and Hold Circuit
  • 19. NEED FOR SAMPLE AND HOLD CIRCUITS  If the input analog voltage of an ADC changes more than ±1/2 LSB, then there is a severe chance that the output digital value is an error.  For the ADC to produce accurate results, the input analog voltage should be held constant for the duration of the conversion.  As the name suggests, a S/H Circuit samples the input analog signal based on a sampling command and holds the output value at its output until the next sampling command is arrived.
  • 20. EXPLANATION SAMPLE AND HOLD CIRCUITS
  • 21. SIMPLE SAMPLE AND HOLD CIRCUITS  The operating principle of a S/H Circuit with the help of a simplified circuit diagram of sample and hold circuit consist of two basic components:  Analog Switch  Holding Capacitor  This circuit tracks the input analog signal until the sample command is changed to hold command. After the hold command, the capacitor holds the analog voltage during the analog to digital conversion.
  • 22. ANALOG SWITCH IN SAMPLE AND HOLD CIRCUITS  Any FET like JFET or MOSFET can be used as an Analog Switch.  The Gate-Source voltage VGS is responsible for switching the JFET.  When VGS is equal to 0V, the JFET acts as a closed switch as it operates in its Ohmic region.  When VGS is a large negative voltage (i.e. more negative than VGS(OFF)), the JFET acts as an open switch as it is cut-off.  The switch can be either a Shunt Switch or a Series Switch, depending on its position with respect to input and output.  The following image shows a JFET configured as both a Shunt Switch and as a Series Switch.
  • 23. TYPES OF SAMPLE AND HOLD CIRCUITS  All the below mentioned circuits use JFET as the switch.  During the sampling period, the JFET is turned ON and the charging in the holding capacitor rises to the level of the input analog voltage.  At the end of the sampling period, the JFET is turned OFF and the holding capacitor is isolated from the input signal.  This makes sure that the output voltage is held constant at the value of the input voltage irrespective of minor changes in the input value.  To compensate for the low drop-out voltage across the holding capacitor, two buffers (voltage followers) are used, one at the input and one at the output.
  • 24. TYPES OF SAMPLE AND HOLD CIRCUITS  The following image shows an open-loop type S/H Circuit.  As there is no feedback, this circuit is relatively faster than the coming circuits (which all are in closed-loop configuration).  But the feedback in the closed-loop architectures provide higher accuracy figures.  The acquisition time (discussed in the next section) must be as low as possible.  It is dependent on three factors:  The RC time constant, where R is the ON Resistance of the JFET (Ron) and C is the holding capacitor CH.  Maximum output current  Slew-rate of the Op-Amp
  • 25. TYPES OF SAMPLE AND HOLD CIRCUITS  A slightly improved circuit than the first one is presented in the next circuit. In this configuration, the ON Resistance of the JFET is brought into the feedback loop and hence, the acquisition time is dependent on the other two factors.
  • 26. TYPES OF SAMPLE AND HOLD CIRCUITS  The next circuit is further improved when compared to the previous circuit by providing voltage gain. The voltage gain of the circuit can be calculated using the input resistor R1 and the feedback resistor RF as follows: A = 1 + (RF / R1)
  • 27. TYPES OF SAMPLE AND HOLD CIRCUITS  The final circuit offers additional advantages than the previous circuit.  The important one is that the position of the holding capacitor is changed and as a result, the voltage at non-inverting terminal of A2 is equal to the voltage across the capacitor divided by the open-loop gain of A2.  This ensure a faster charging time of the holding capacitor and subsequently a shorter acquisition time.
  • 28. PERFORMANCE PARAMETERS OF S&H CIRCUITS  The performance of an S/H Circuit can be characterized by parameters that are commonly used for an amplifier like Input Offset Voltage, Gain Error, Non-linearity and so on.  But there are a few characteristics that are specific to the S/H Circuits.  These characteristics are helpful in analyzing its performance during the transition from sampling mode to hold mode (and vice versa) and also during hold mode operations.
  • 29. PERFORMANCE PARAMETERS OF S&H CIRCUITS Acquisition Time (tac):  The time required for the charge in the holding capacitor to rise up to a level that is close to the input voltage during the sampling is called acquisition time. It is affected by three factors:  The RC Time Constant  The Slew-Rate of the Op-Amp  The maximum output current of the Op-Amp
  • 30. PERFORMANCE PARAMETERS OF S&H CIRCUITS Aperture Time (tap)  The time delay between the initiation of VO tracking the Vi and the initiation of the hold command is called the Aperture Time. This delay is usually due to the propagation delays through the driver and the switch circuits.  For a precise timing operation, the hold command must be initiated in advance by an amount of aperture time. Aperture Uncertainty (∆ tap)  The Aperture time will not be the same for all the sample and will vary from sample to sample. This uncertainty is called Aperture Uncertainty. This will severely affect the advancing of the hold command.
  • 31. PERFORMANCE PARAMETERS OF S&H CIRCUITS Hold Mode Settling Time (ts)  The hold mode settling time is the time taken by the output VO to settle within the specified error band (usually 1%, 0.1% or 0.01%) after the application of hold command. Hold Step  During the switching from sample mode to hold mode, there might an unwanted transfer of charge between the switch and the holding capacitor (mainly due to the parasitic capacitances). This will affect the capacitor voltage as well as the output voltage. This change in the output voltage from the desired voltage is called Hold Step.
  • 32. PERFORMANCE PARAMETERS OF S&H CIRCUITS Feedthrough  Again, the parasitic capacitances in the switch may cause AC coupling between VO and Vi in hold mode. As a result, the output voltage may vary with changes in the input voltage and this is referred to as feedthrough. Droop  Voltage Droop is a phenomenon where the voltage across the holding capacitor drops down due to leakage currents.
  • 33. ADVANTAGES OF S&H CIRCUITS Advantages of Sample and Hold Circuit  The main and important advantage of a typical SH Circuit is to aid an Analog to Digital Conversion process by holding the sampled analog input voltage.  In multichannel ADCs, where synchronization between different channels is important, an SH circuit can help by sampling analog signals from all the channels at the same time.  In multiplexed circuits, the crosstalk can be reduced with an SH circuit.
  • 34. APPLICATIONS OF S&H CIRCUITS Applications of Sample and Hold Circuit  Some of the important applications are mentioned below:  Analog to Digital Converter Circuits (ADC)  Digital Interface Circuits  Operational Amplifiers  Analog De-multiplexers  Data distribution systems  Storage of outputs of multiplexers  Pulse Modulation Systems
  • 35. QUANTIZATION  Quantization, in mathematics and digital signal processing, is the process of mapping input values from a large set (often a continuous set) to output values in a (countable) smaller set, often with a finite number of elements.  Rounding and truncation are typical examples of quantization processes.  Quantization is involved to some degree in nearly all digital signal processing, as the process of representing a signal in digital form ordinarily involves rounding.  Quantization also forms the core of essentially all lossy compression algorithms.
  • 36. QUANTIZATION – EXPLANATION  The simplest way to quantize a signal is to choose the digital amplitude value closest to the original analog amplitude.  This example shows the original analog signal (green), the quantized signal (black dots), the signal reconstructed from the quantized signal (yellow) and the difference between the original signal and the reconstructed signal (red).  The difference between the original signal and the reconstructed signal is the quantization error and, in this simple quantization scheme, is a deterministic function of the input signal.
  • 37. PROCESS  The following figure represents an analog signal.  This signal to get converted into digital, has to undergo sampling and quantizing.  The quantizing of an analog signal is done by discretizing the signal with a number of quantization levels. Quantization is representing the sampled values of the amplitude by a finite set of levels, which means converting a continuous-amplitude sample into a discrete-time signal.
  • 38. PROCESS  The following figure shows how an analog signal gets quantized. The blue line represents analog signal while the brown one represents the quantized signal.  Both sampling and quantization result in the loss of information. The quality of a Quantizer output depends upon the number of quantization levels used.
  • 39. PROCESS  The discrete amplitudes of the quantized output are called as representation levels or reconstruction levels. The spacing between the two adjacent representation levels is called a quantum or step-size.  The following figure shows the resultant quantized signal which is the digital form for the given analog signal.  This is also called as Stair-case waveform, in accordance with its shape.
  • 40. TYPES OF QUANTIZATION  There are two types of Quantization - Uniform Quantization and Non- uniform Quantization.  The type of quantization in which the quantization levels are uniformly spaced is termed as a Uniform Quantization.  The type of quantization in which the quantization levels are unequal and mostly the relation between them is logarithmic, is termed as a Non-uniform Quantization.
  • 41. UNIFORM QUANTIZATION  There are two types of uniform quantization. They are Mid-Rise type and Mid-Tread type.  The following figures represent the two types of uniform quantization  Figure 1 shows the mid-rise type and figure 2 shows the mid-tread type of uniform quantization.
  • 42. QUANTIZATION ERROR  For any system, during its functioning, there is always a difference in the values of its input and output.  The processing of the system results in an error, which is the difference of those values.  The difference between an input value and its quantized value is called a Quantization Error.  A Quantizer is a logarithmic function that performs Quantization rounding off the value.  An analog-to-digital converter (ADC) works as a quantizer.
  • 43. QUANTIZATION ERROR  The following figure illustrates an example for a quantization error, indicating the difference between the original signal and the quantized signal.
  • 44. QUANTIZATION NOISE  It is a type of quantization error, which usually occurs in analog audio signal, while quantizing it to digital.  For example, in music, the signals keep changing continuously, where regularity is not found in errors.  Such errors create a wideband noise called as Quantization Noise