Explains the basics of Digital Signal Processing

1. DIGITAL SIGNAL PROCESSING – An
Introduction
Dr.Y. Narasimha Murthy Ph.D
yayavaram@yahoo.com

2. Organization
o What is signal processing
o Need of Processing
o Catagories
o Advantages of Digital over analog
o Filters-Analog & Digital
o Comparison
o Digital filters-Types
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3. contd
o FIR &IIR
o Advantages-Disadvantages
o Applications of DSP
o Simple Illustrations
o Various types of DSPs
o Microprocessor & Signal processor
o Architecture
o Books &Web resources
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4. What is Signal processing?
 Signal processing is the analysis,
interpretation, and manipulation of signals
like sound, images time-varying
measurement values and sensor data etc…
 For example biological data such as
electrocardiograms, control system signals,
telecommunication transmission signals such
as radio signals, and many others.
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5. Need of Signal Processing
When a signal is transmitted from one point
to another there is every possibility of
contamination /deformation of the signal
by external noise.
So to retrieve the original signal at the
receiver suitable filters are to be used. i.e
the signal is processed to obtain the pure
signal.
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6. Categories of signal processing
 Analog signal processing — for signals that
have not been digitized, as in classical
radio, telephone, radar, and television
systems.
 This involves linear electronic circuits such
as passive filters, active filters, additive
mixers, integrators and delay lines.
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7.  It also involves non-linear circuits such as
compandors, multiplicators (frequency mixers
and voltage-controlled amplifiers), voltage-
controlled filters, voltage-controlled oscillators
and phase-locked loops.
 Digital signal processing — for signals that have
been digitized, processing is done by general-
purpose computers or by digital circuits such as
ASICs, field-programmable gate arrays or
specialized digital signal processors (DSP chips).
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8. So the processing of the signal helps to estimate
characteristic parameters of the signal and also to
transform the signal in to the desired form.
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9. Analog signal processing
The analog signal processing is basically, filtering of
the signal . It can be denoted by the following
diagram.
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10. Digital signal processing-Block diagram
The digital signal processor consists of anti-aliasing
filter, analog to digital converter (ADC), a digital filter
represented by the transfer function H(z), a digital to
analog converter and a reconstruction filter.
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11. Advantages of Digital over analog
signal processing
 Accuracy: The analog circuits are prone to
temperature and external effects, but the digital
filters have no such problems.
 Flexibility: Reconfiguration of analog filters is
very complex whereas the digital filters can be
reconfigured easily by changing the program
coefficients.
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12.  Digital signals can be easily stored on any
magnetic media or optical media are using
semiconductor chips.
 Easy operation: Even complex
mathematical operations can be performed
easily using computers, which is not the
case with analog processing.
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13.  Multiplexing: Digital signal processing
provides the way for Integrated service
digital network (ISDN) where digitized
signals can be multiplexed with other
digital data and transmitted through the
same channel.
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14. Limitations
There are also certain limitations in DSP.
 Bandwidth restrictions
 Speed limitations
 Finite word length problems.
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15. Filters
Any one who observes the DSP block
diagram finds that the filter is the main
component of DSP.
Filters have two uses
a) Signal separation
b) Signal restoration
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16.  Signal separation is needed when a signal
has been contaminated with interference,
noise or other signals.
 Signal restoration is used when a signal
has been distorted in some way or other.
For example an audio recording made with
poor equipment may be filtered to get the
original sound.
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17. Another example of deblurring of an image
occurred with an improperly focused lens
or a shaky camera.
So these problems can be solved with either
analog or digital filters.
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18. Analog filters
Analog filters take the analog signal as input
and process the signal and finally gives the
analog output.
An analog filter is constructed using resistors,
capacitors, active components etc…
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19. A simple analog low pass filter is shown
below
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20. Coming to advantages of Analog filters they are
cheap and have a large dynamic range in
both amplitude and frequency. But in terms of
performance they are not superior to digital
filters.
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21. Digital filters
A digital filter processes and generates digital
data.
A digital filter constitutes elements like adder,
multiplier and delay units.
Digital filters are vastly superior in the level of
performance in comparison to analog filters.
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22. A simple digital filter
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23. Advantages
There are many advantages with digital
filters.
 Unlike analog filters ,the digital filter
performance is not influenced by
component ageing, temperature and power
variations.
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24.  A digital filter is highly immune to noise and
relatively stable.
 Digital filters afford a wide variety of shapes
for the amplitude and phase responses.
 Impedance matching problems are minimum.
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25.  Transportation and reconfiguration is very
easy ,which is not true in the case of analog
filters.
 Multiple filtering is possible only in digital
filters.
 Computational problems are minimum.
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26. Disadvantages:
There are few disadvantages also.
 Quantization error occurs due to finite word
length in the representation of signals and
parameters.
 Digital filters also suffer from Bandwidth
problems.
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27. Differences between analog and
digital filters :
 An analog filter is constructed using active,
passive components like resistors, capacitors
and op amps etc..
A digital filter constitutes adder, multiplier and
delay elements
 An analog filter is denoted by a differential
equation.
A digital filter is denoted by a difference
equation.
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28.  Laplace transform is used for the analysis of
analog filter.
Z transforms are used for the analysis of digital
filters.
 The frequency response of an analog filter can
be modified by changing the components.
The frequency response can be changed by
changing the filter coefficients.
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29. Types of Digital filters
Broadly speaking ,two types of digital filters
exists.
 FIR Filters(Finite impulse response filters)
 IIR Filters (Infinite Impulse response filters)
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30. FIR Filters
The digital filter whose impulse response is of finite
duration is known as Finite impulse response filter.
The response of the FIR filter depends only on the
present and past input samples.
These FIR filters are also called non recursive filters.
So, in FIR the impulse response sequence is of finite
duration, i.e. it has a finite number of non-zero terms.
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31. The system with the impulse response
denotes an FIR system.


 

otherwise
n
n
h
0
4
2
)
(
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32. Ex: The following difference equation
denotes the finite impulse response filter.
For i<0, y(n)=0 i.e. the impulse response is
finite and it exists only for n>0
)
(
)
(
1
0
i
n
x
b
n
y
N
i
i 
 


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33. Advantages of FIR Filters
 FIR filters can be designed with exact linear
phase. These linear phase filters are
important for applications where frequency
dispersion due to non-linear phase is
hazardous. (For example speech processing
and data transmission)
 FIR filters are stable
 Round off noise can be eliminated in FIR
filters
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34.  FIR filters can be efficiently implemented in
multirate DSP systems
 FIR filters reduce the computation complexity
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35. Disadvantages
 As large number of impulse response
samples are required to properly
approximate sharp cutoff FIR filters the
processing will become complex due to slow
convolution.
 The delay of linear phase FIR filters can
sometimes create problems in some DSP
applications.
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36. IIR Filters
The digital filter whose impulse response is of infinite
duration is known as Infinite impulse response filter.
The response of an IIR filter is a function of
current and past input signal samples and past
output signal samples.
It is also called recursive filter.

 





K
k
k
L
l
l k
n
y
B
l
x
x
A
n
y
1
0
)
(
)
(
)
(
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37. Ex: A simple first order difference equation
illustrates the IIR filter.
The implementation diagram of first order IIR
filter is shown in the next slide.
)
1
(
.
)
(
)
( 

 n
y
b
n
x
n
y
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38. 2/28/2023 Dr.YNM 38

39. Advantages of IIR filters
1. An IIR filter has lesser number of side
lobes in the stop-band than an FIR filter
with the same number of parameters.
2. Also the implementation of an IIR filter
involves fewer parameters, less
memory requirements and lower
computational complexity.
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40. Disadvantages
 IIR filters do not have linear phase and
also they are not very stable.
 Realization of IIR filters is not very easy
as compared to FIR filters
 As it is a recursive filter the number of
coefficients is very large and the memory
requirements are also high
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41. Applications of DSP
Digital signal processing has variety of
applications in diverse fields like
 Digital filtering
 Spectral analysis
 Speech processing
 Image processing
 Radar and sonar processing
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42.  Disk and robot control
 Telecommunication
 Consumer electronics
 Biomedical engineering
 Military applications
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43. Let us discuss few examples of DSP in
musical sound processing.
In all musical recordings, the sound from
instruments is recorded in studio and
then special audio effects are added by
manipulating the recorded musical
sounds. The audio effects are artificially
generated using various DSP
techniques.
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44. The sound reaching the listeners in a
concert hall during a musical programme
consists of direct sound, early reflections
and reverberations (echoes). But the
sound recorded in a studio is different
and it doesn’t sound natural.
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45. So, echoes are simply generated by delay
units. The direct sound and a single echo
appear in K sampling period latter can be
generated by the FIR filter with the system
function
The realization of the echo filter is shown in the
next slide.
1
,
.
1
)
( 

 
b
Z
b
z
H K
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46. 2/28/2023 Dr.YNM 46

47. To generate multiple echoes separated K
sapling periods we can use an FIR filter
with transfer function
K
N
N
K
K
Z
b
Z
b
Z
b
z
H )
1
(
1
2
2
,
.
1
)
( 







 

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48. Similarly an infinite number of echoes
spaced K sampling periods apart with
exponentially decaying amplitudes can
be created by an IIR filter.
The realization of infinite echo generator is
shown in the next slide.
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49. 2/28/2023 Dr.YNM 49

50. The other special sound effects are
flanging and chorus. The flanging effect
is created by feeding the same musical
note to two tape recorders and then
combining their delayed outputs. This
effect can be simulated using the FIR
filter by periodically varying the delay
K(n) between 0 and K.
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51. The functional diagram of flanging effect
generator is shown in the next slide.
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52. 2/28/2023 Dr.YNM 52

53. The chorus effect is achieved when
several musicians are playing the same
musical note at the same time with small
changes in the amplitudes and small
timing differences between their sounds.
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54. A chorus generator can be realized by
parallelly connecting few number of
flanging effect filters.
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55. Various DSP Processors
Texas DSP Processors
16-bit Fixed point arithmetic processors
 TMS320C1X
 TMS320C2X
 TMS320C5X
 TMS320C8X
32-bit floating point arithmetic processors
 TMS320C3X
 TMS320C4X
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56. Analog devices DSP Processors
 Blackfin
 SHARC
 TigerSHARC
 ADSP-21XX – 16 bit fixed point processor
 ADSP-210XX- 32 bit floating point processor
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57. Differences between microprocessor
and Digital signal processor
 A microprocessor with its limited speed
is meant for low speed applications
whereas the DSP is meant for fast real
time applications.
 Generally microprocessors use Van-
nuemann architecture whereas most of
the DSP processors use a modified
Harvard architecture with two or three
memory buses.
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58. OR
Bus
General purpose processors
Early DSP processors
More optimized DSP processors
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59. Simple architecture of DSP
processor
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60. The books which have helped me to
understand DSP
1. Oppenheim, A.V. and Schefar, Digital signal
processing, PHI
2. Oppenheim, Applications of digital signal
processing, PHI
3. Rabir and Gold, Theory of digital signal
processing, PHI
4. Proakis and Manolakis, Digital signal
processing, Pearson publishers
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61. 5. Antoniou, A. Digital filters analysis, design
applications, McGraw Hill
6. Johnson, J.R. Introduction to digital signal
processing , PHI
7. Vanvalkenburg.M.V. Analog filter design,
Sanders publishers
8. Vinay K. Ingle, Proakis, Digital signal
processing using MATLAB, Bookware series
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62. 9. Sajeeth K. Mithra, Digital signal processing,
TMH
10. V.K. Khanna, Digital signal processing,
telecommunication, multimedia technology,
Wheeler publishers
11. P. Rameshbabu, Digital signal processing,
Scitech publishers.
12. Salivana, Digital signal processing, TMH
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63. 13. Ifeachor and Jervis, Digital signal
processing-a practical approach, Addison
Wesley publishers
14. Sarkar N. Elements of digital signal
processing, Kanna publishers
15. Defetta D.J. Digital signal processing, John
Wieley publishers
16. Lyons R.G. Understanding digital signal
processing,Addition Wesley
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64. 17. B. Venkataramani, Digital signal
processors, TMH
18. Chapman J. Stephen, MATLAB
Programming for engineers, Bookware
Series
19. Ramachandran.B. Digital signal processing,
Anuradha publishers
20. Bose N.K. Digital filters-Theory and applications,
Elsevier publishers
21. The Scientist and Engineer's and Guide to Digital Signal
Processing by Steven W. Smith.(On line text)
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65. Web References
 www.ti.com
 www.analog.com
 www.dspguru.com
 www.mathworks.com
 www.dsptutor.freeuk.com
 www.dspguide.com
 www.elsevier.com/locate/dsp (On line journal)
 dsp.rice.edu (rice university)
 www.youtube.com (lecture on DSP)
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66. Concluding Remarks
The woods are lovely, dark and deep,
But I have promises to keep,
And miles to go before I sleep,
And miles to go before I sleep.
---- Robert Frost
GOOD LUCK!
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