Download Introduction to DSP

Engr. Hinesh Kumar
Lecturer, I.B.T, LUMHS
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Signal
Signal Classification
Signal Processing
Concept of Systems
DSP
Elements of DSP
Advantages of DSP
Limitations
Applications
• A word ‘Signal’ comes from latin ‘Signum’ which means
‘Sign’.
• “ A signal is a quantity or effect such as current or voltage
that can be varied in such a way as to convey information.”
OR
• “ A signal is defined as a mathematical function that
conveys information about the state or behavior of a
physical system.”
• Examples: electrical current, voltage, force, speed,
speech, music, picture and video signals etc
Analog
Time
Amplitude
Continuous
Continuous
VS
Digital
Discrete
Discrete
• An analog or analogue signal is any continuous signal
for which the time varying feature.
• An analog signal is a signal that exists at every instant of
time
• A continuous signal is often referred to as continuous time
or analog.
• The independent variable is a continuous variable
• Continuous signal can assume any value over a
continuous range of numbers
• It is a special form of discrete
discrete in time and amplitude.
• A digital signal is acquired
sampled analog value into a
(quantization).
• These signals are called digital
are represented by digits.
time signal which is
by representing the
finite set of values
because the samples
Representation, transformation and manipulation
of signals and the information they contain.
Signal operation include:
(1) Transform, filter, inspection, spectrum analysis;
(2) Modulation and coding;
(3) Analog Signal Processing;
(4) Digital Signal Processing.
Computer, Semiconduct and Information Science
1960’s-1970’s
System
Device or technology of signal processing
Analog System
System with analog input and output.
 Digital System
System with digital input and output.
Acoustic
domain
Electric
domain
Acoustic
domain
Continuous-time system: the input and output signals
are continuous time
Acoustic
domain
Electric
domain
Acoustic
domain
Digital domain
Discrete-time system has discrete-time input and output
signals
Acoustic
domain
Electrical
domain
Digital
domain
Electrical
domain
Acoustic
domain
Analog Computer
a bit loud
a bit loud
Digital Computer
DSP
DAC
ADC
1010
1001
OUTPUT
• Converting a continuously changing waveform (analog) into a
series of discrete levels (digital).
• The analog waveform is sliced into equal segments and the
waveform amplitude is measured in the middle of each segment
• The collection of measurements make up the digital
representation of the waveform
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A basic DSP system is composed of:
An ADC providing digital samples of an analog input
A Digital Processing system
A DAC converting processed samples to analog output
Real-time signal processing: All processing operation must
be complete between two consecutive samples
Analog Signal Processing
Sensor
Analog Signal
Conditioning
Digital Signal Processing
ADC
Digital Signal
Conditioning
DSP
DAC
1. An analog input
2. An analog filter,
3. An analog-to-digital conversion (ADC) unit,
4. A digital signal (DS) processor,
5. A digital-to-analog conversion (DAC) unit,
6. and a reconstruction (anti-image) filter.
• The analog input signal, which is continuous in
• time and amplitude.
• It is the signal generated from some transducer or
some communication system.
• Examples of such analog signals include current,
voltage, temperature, pressure.
• It may be biomedical signal like ECG or EEG.
• Generally it is analog in nature. It is denoted by x(t).
• This is basically a low pass filter.
• It is used for the following purposes.
It removes the high frequency noise contained in input
signal.
As the name indicates, it avoids aliasing effect. That
means it is used to band limit the signal.
• The band-limited signal at the output of the analog
filter is then sampled and converted into the digital
signal, which is discrete both in time and in
amplitude.
• This is required because digital signal processor
accepts the signal which is digital in nature.
• It processes input signal digitally.
• In a simple language processing of input signal means
modifying the signal as per requirement.
• It consists of lowpass, highpass, and bandpass digital
filtering, or other algorithms for different applications.
• DS processor is a special type of digital computer
consists of , a microprocessor, or an advanced
microcontroller; and
can be implemented using
software in general.
• The DAC unit, converts the output of the digital signal
processor into an analog output signal.
• The signal is continuous in time and discrete in
amplitude.
• Output signal of DAC is an analog, that means it is a
continuous signal.
• It may contain high frequency components which are
unwanted.
• To remove these components, reconstruction filter is
used.
1. Versatility
Digital systems can be reprogrammed for multiple
applications ( where programmable DSP chips are
used). Moreover, digital systems can be ported to
different hardware
2. Repeatability
Digital systems can be easily duplicated. These
systems do not depend upon component tolerances and
temperature.
3. Simplicity:
It is easy to built any digital system as compared
to an analog one.
4. Accuracy:
To design an analog system, analog components
like resistors, capacitors and inductors are used.
The tolerance of these components reduce accuracy of
the system.
While in case of DSP; much better accuracy is obtained.
5. Remote Processing
Analog signals are difficult to store because of
problems like noise and distortion.
While digital signal can be easily stored on storage
media like magnetic tapes, disks etc.
Thus as compared to analog signals digital signals can
be easily transposed.
So remote processing of digital signal can be done
easily.
6. Implementation of algorithms:
The mathematical processing algorithms can be
easily implemented in case of digital signal processing.
But such algorithms are difficult to implement in case of
analog signals.
7. Easy Up gradations:
Because of the use of software, digital signal
processing systems can be easily upgraded as
compared to analog systems.
8. Compatibility:
In case of digital systems, generally all
applications needs standard hardware.
Thus operation of DSP system is mainly dependent on
software.
Hence universal compatibility is possible as compared to
analog systems.
9. Cheaper:
In many applications, the digital systems are
comparatively cheaper than analog systems.
1. System Complexity:
DSP system needs use of converters like ADC and
DAC.
This increases the system complexity compared to
analog systems. Similarly in many applications, the time
required for this conversion is more.
• Bandwidth Limitation:
In case of DSP system, if input signal is having
wide bandwidth then it demands for high speed ADC.
This is because to avoid aliasing effect, the sampling
rate should be at least twice the bandwidth.
Thus such signals require fast digital signal processors.
But always there is practical limitation in the speed of
processors and ADC.
3. Power Consumption:
A typical digital signal processing chip contains
more than four lakh transistors.
Thus power dissipation is more in DSP systems as
compared to analog systems
4. For small applications digital signal processing
systems are expensive as compared to analog
systems
MILITARY
IMAGE PROCESSING
INSTRUMENTATION &Secure
CONTROL
communication
Pattern recognition
Spectrum analysis
Radar processing
Robotic vision
Sonar processing
Image enhancementPosition and rate control
applications
Noise reduction
Missile guidance
Satellite Consumer
weather map
SPEECHdigital,
& AUDIO
cellar
mobile phones
Data compression
animation
Speech
recognition
universal
mobile telecommunication system
Speech
synthesis
digital
television
TELECOMMUNICATION
Text digital
to speech
camera
Echo cancellation
digitalinternet
audio music, phonesAdaptive
and video
equalization
digital answer machines,
faxconferencing
and modems
Video
voice mail system
Biomedical
data communication
interactive entertainment systems
Patient monitoring
Scanners
ECG (Electrocardiograph)
X-ray storage/enhancement