Data Converters Short notes | Digital Circuits - Electronics and Communication Engineering (ECE) PDF Download

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Data Converters Notes
Introduction
Data converters are electronic circuits that bridge the analog and digital domains
b y converting signals between analog and digital formats. They are essential in
modern electronics, enabling communication between analog real-world signals
and digital processing systems.
K ey Concepts
• Analog-to-Digital Converter (ADC) : Converts continuous analog signals
into discrete di gital values.
• Digital-to-Analog Converter (D A C) : Converts digital data into continuous
analog sig nals.
• Applications : Used in audio processing, telecommunications, sensors, and
control sys tems.
Basic Principles
• Sampling : In ADCs, the analog signal is sampled at regular intervals, de-
fined b y the sampling frequency f
s
. Per the Nyquist theorem, f
s
= 2f
m
,
wheref
m
is the signal’ s highest frequency .
• Quantization : The sampled analog signal is mapped to discrete levels, in-
troducing quantization error: Q
e
=
V
FS
2
N
, whereV
FS
is the full-scale voltage
andN is the number of bits.
• Resolution : Number of bits (N ) determines the precision, with 2
N
levels.
HigherN reduces quantization error .
Types of Data Converters
• ADC Types :
– Flash ADC : Uses compar ators for high-speed conversion, resolution
limited b y hardware complexity .
– Successive Appr oximation Register (S AR) ADC : Iter atively approximates
the input, balancing speed and resolution.
– Delta-Sigma ADC : Oversamples and uses noise shaping for high reso-
lution, ideal for audio.
– Pipelined ADC : Stages process bits sequentially , offering high speed and
moder ate resolution.
• D A C Types :
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Page 2


Data Converters Notes
Introduction
Data converters are electronic circuits that bridge the analog and digital domains
b y converting signals between analog and digital formats. They are essential in
modern electronics, enabling communication between analog real-world signals
and digital processing systems.
K ey Concepts
• Analog-to-Digital Converter (ADC) : Converts continuous analog signals
into discrete di gital values.
• Digital-to-Analog Converter (D A C) : Converts digital data into continuous
analog sig nals.
• Applications : Used in audio processing, telecommunications, sensors, and
control sys tems.
Basic Principles
• Sampling : In ADCs, the analog signal is sampled at regular intervals, de-
fined b y the sampling frequency f
s
. Per the Nyquist theorem, f
s
= 2f
m
,
wheref
m
is the signal’ s highest frequency .
• Quantization : The sampled analog signal is mapped to discrete levels, in-
troducing quantization error: Q
e
=
V
FS
2
N
, whereV
FS
is the full-scale voltage
andN is the number of bits.
• Resolution : Number of bits (N ) determines the precision, with 2
N
levels.
HigherN reduces quantization error .
Types of Data Converters
• ADC Types :
– Flash ADC : Uses compar ators for high-speed conversion, resolution
limited b y hardware complexity .
– Successive Appr oximation Register (S AR) ADC : Iter atively approximates
the input, balancing speed and resolution.
– Delta-Sigma ADC : Oversamples and uses noise shaping for high reso-
lution, ideal for audio.
– Pipelined ADC : Stages process bits sequentially , offering high speed and
moder ate resolution.
• D A C Types :
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– W eighted Resistor D A C : Uses resistors scaled b y binary weights, simple
but sensitive to resistor mismatch.
– R-2R Ladder D A C : Uses a resistor network for better accur acy and scal-
ability .
– Delta-Sigma D A C : Emplo ys oversampling for high precision, common
in audio applications.
Performance Metrics
• Resolution : Number of bits (N ), e.g., 8-bit ADC has2
8
=256 levels.
• Sampling Rate : Frequency of sampling (f
s
), measured in samples per sec-
ond (SPS).
• Signal-to-Noise Ratio (SNR) : Ratio of signal power to noise power , in dB:
SNR=6.02N +1.76 (ideal ADC).
• T otal Harmonic Distortion (THD) : Measures distortion introduced b y non-
linearities.
• Effective Number of Bits (ENOB) : Effective resolution considering noise
and distortion: ENOB=
SINAD-1.76
6.02
, where SINAD is signal-to-noise-and-distortion
r atio.
K ey Equations
• Quantization Step Size : ?=
V
FS
2
N
.
• Quantization Noise Power : P
Q
=
?
2
12
.
• D A C Output V oltage : F or anN -bit D A C,V
out
=V
ref
·
D
2
N
, whereD is the digital
input andV
ref
is the reference voltage.
Pr actical Consider ations
• Nonlinearities : Differential nonlinearity (DNL) and integr al nonlinearity
(INL) affect accu r acy .
• Power Consumption : Higher resolution and sampling r ates increase power
usage.
• Anti-Aliasing Filter : Required before ADC to prevent aliasing b y limiting
input frequencies tof <
fs
2
.
• Reconstruction Filter : Smooths D A C output to remove high-frequency com-
ponents.
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