SlideShare a Scribd company logo
1 of 42
1
Digital Signal
Processing (DSP)
Lecture no 1
Discrete-Time Signals and Systems
Introduction to Signals and
Systems
Continued
Continued
Continued
Continued
Continued
Continued
Continued
Continued
Continued
Continued
14
Sum of two sequences
Product of two sequences
Multiplication of a sequence by a numberα
Delay (shift) of a sequence
Basic Sequence Operations
]
[
]
[ n
y
n
x 
integer
:
]
[
]
[ 0
0 n
n
n
x
n
y 

14
]
[
]
[ n
y
n
x 
]
[n
x


15
Basic sequences
Unit sample sequence
(discrete-time impulse,
impulse)
 






0
1
0
0
n
n
n

7/6/2023
15
16
Basic sequences
Unit step sequence






0
0
0
1
]
[
n
n
n
u
7/6/2023
16
 




n
k
k
n
u 
]
[











0
]
[
]
2
[
]
1
[
]
[
]
[
k
k
n
n
n
n
n
u 


 
]
1
[
]
[
]
[ 

 n
u
n
u
n
 First backward difference
  
  
0, 0 ,
1, 0
0 0
1 0
since
n
k
when n
k
when n
k
k
k



 


 

 

 


 

17
Basic Sequences
Exponential sequences
n
A
n
x 

]
[
7/6/2023
17
A and α are real: x[n] is real
A is positive and 0<α<1, x[n] is positive and
decrease with increasing n
-1<α<0, x[n] alternate in sign, but decrease
in magnitude with increasing n
 : x[n] grows in magnitude as n increases
1


18
EX. 1 Combining Basic sequences






0
0
0
]
[
n
n
A
n
x
n

7/6/2023
18
If we want an exponential sequences that is
zero for n <0, then
]
[
]
[ n
u
A
n
x n


Cumbersome
simpler
19
Periodic Sequences
A periodic sequence with integer period N
n
all
for
N
n
x
n
x ]
[
]
[ 

   

 


 N
w
n
w
A
n
w
A 0
0
0 cos
cos
7/6/2023
19
integer
,
2
0 is
k
where
k
N
w 

0
2 / , integer
N k w where k is


1.2
20
21
Discrete-Time System
Discrete-Time System is a trasformation
or operator that maps input sequence
x[n] into a unique y[n]
y[n]=T{x[n]}, x[n], y[n]: discrete-time
signal
7/6/2023
21
T{‧}
x[n] y[n]
Discrete-Time System
22
EX. 5 The Ideal Delay System






 n
n
n
x
n
y d ],
[
]
[
7/6/2023
22
If is a positive integer: the delay of the
system. Shift the input sequence to the
right by samples to form the output .
d
n
d
n
If is a negative integer: the system will
shift the input to the left by samples,
corresponding to a time advance.
d
n
d
n
23
Properties of Discrete-time systems
Memoryless (memory) system
24
Properties of Discrete-time systems
Linear Systems
7/6/2023
24
 If  
n
y1
T{‧}
 
n
x1
 
n
y2
 
n
x2
T{‧}
 
n
ay
 
n
ax T{‧}
     
n
bx
n
ax
n
x 2
1
3 
      
n
by
n
ay
n
y 2
1
3 

T{‧}
   
n
y
n
y 2
1 
   
n
x
n
x 2
1  T{‧} additivity property
homogeneity or scaling
property
 principle of superposition
 and only If:
25
Example Nonlinear Systems
7/6/2023
25
Method: find one counterexample
 2
2
2
1
1
1
1 


 counterexample
   2
]
[n
x
n
y 
 For
   
]
[
log10 n
x
n
y 
   
1
10
log
1
log
10 10
10 


 counterexample
 For
26
Properties of Discrete-time systems
Time-Invariant Systems
Shift-Invariant Systems
7/6/2023
26
   
0
1
2 n
n
x
n
x 
    
0
1
2 n
n
y
n
y 

 
n
y1
T{‧}
 
n
x1
T{‧}
28
29
Properties of Discrete-time systems
Causality
A system is causal if, for every choice
of , the output sequence value at
the index depends only on the
input sequence value for
0
n
0
n
n 
7/6/2023
29
0
n
n 
30
Ex:9 Example for Causal System
Forward difference system is not Causal
Backward difference system is Causal
     
n
x
n
x
n
y 

 1
     
1


 n
x
n
x
n
y
7/6/2023
30
32
Properties of Discrete-time system
Stability
Bounded-Input Bounded-Output (BIBO)
Stability: every bounded input sequence
produces a bounded output sequence.
  n
all
for
B
n
x x ,



  n
all
for
B
n
y y ,



7/6/2023
32
if
then
33
Ex:10 Test for Stability or Instability
   2
]
[n
x
n
y 
  n
all
for
B
n
x x ,



  n
all
for
B
B
n
y x
y ,
2




7/6/2023
33
if
then
is stable
34
Accumulator system    




n
k
k
x
n
y
    bounded
n
n
n
u
n
x :
0
1
0
0







Ex:11 Test for Stability or Instability
7/6/2023
34
     








 
 



bounded
not
n
n
n
k
x
k
x
n
y
n
k
n
k
:
0
1
0
0
Accumulator system is not stable
35
Linear Time-Invariant (LTI)
Systems
Impulse response
7/6/2023
35
 
0
n
n 

 
n
h
 
n

 
0
n
n
h 
T{‧}
T{‧}
36
LTI Systems: Convolution
     






k
k
n
k
x
n
x 
         
 
       


























k
k
k
n
h
n
x
k
n
h
k
x
k
n
T
k
x
k
n
k
x
T
n
y 

7/6/2023
36
Representation of general sequence as a
linear combination of delayed impulse
principle of superposition
An Illustration Example(interpretation 1)
38
Properties of LTI Systems
Convolution is commutative
       
n
x
n
h
n
h
n
x 


7/6/2023
38
h[n]
x[n] y[n]
x[n]
h[n] y[n]
     
         
n
h
n
x
n
h
n
x
n
h
n
h
n
x 2
1
2
1 





Convolution is distributed over addition
39
Cascade connection of systems
     
n
h
n
h
n
h 2
1 

7/6/2023
39
x [n] h1[n] h2[n] y [n]
x [n] h2[n] h1[n] y [n]
x [n] h1[n] ]h2[n] y [n]
40
Parallel connection of systems
     
n
h
n
h
n
h 2
1 

7/6/2023
40
41
Stability of LTI Systems
LTI system is stable if the impulse response
is absolutely summable .
  

 



k
k
h
S
41
Causality of LTI systems   0
,
0 
 n
n
h
HW: proof, Problem 2.62
End chapter problems
1.1, 1.2,
 Example 2.33,
2.6a, 2. 7, 2.17 a b,
42

More Related Content

Similar to DSP Lec 1.ppt

A novel approach for high speed convolution of finite and infinite length seq...
A novel approach for high speed convolution of finite and infinite length seq...A novel approach for high speed convolution of finite and infinite length seq...
A novel approach for high speed convolution of finite and infinite length seq...
eSAT Journals
 
1 Aminullah Assagaf_Estimation-of-domain-of-attraction-for-the-fract_2021_Non...
1 Aminullah Assagaf_Estimation-of-domain-of-attraction-for-the-fract_2021_Non...1 Aminullah Assagaf_Estimation-of-domain-of-attraction-for-the-fract_2021_Non...
1 Aminullah Assagaf_Estimation-of-domain-of-attraction-for-the-fract_2021_Non...
Aminullah Assagaf
 
Simple Comparison of Convergence of GeneralIterations and Effect of Variation...
Simple Comparison of Convergence of GeneralIterations and Effect of Variation...Simple Comparison of Convergence of GeneralIterations and Effect of Variation...
Simple Comparison of Convergence of GeneralIterations and Effect of Variation...
Komal Goyal
 

Similar to DSP Lec 1.ppt (20)

MVPA with SpaceNet: sparse structured priors
MVPA with SpaceNet: sparse structured priorsMVPA with SpaceNet: sparse structured priors
MVPA with SpaceNet: sparse structured priors
 
Chap 2 discrete_time_signal_and_systems
Chap 2 discrete_time_signal_and_systemsChap 2 discrete_time_signal_and_systems
Chap 2 discrete_time_signal_and_systems
 
Chapter-3.pptx
Chapter-3.pptxChapter-3.pptx
Chapter-3.pptx
 
ch2-3
ch2-3ch2-3
ch2-3
 
Lecture 4: Classification of system
Lecture 4: Classification of system Lecture 4: Classification of system
Lecture 4: Classification of system
 
lecture4signals-181130200508.pptx
lecture4signals-181130200508.pptxlecture4signals-181130200508.pptx
lecture4signals-181130200508.pptx
 
Module v sp
Module v spModule v sp
Module v sp
 
Intro Class.ppt
Intro Class.pptIntro Class.ppt
Intro Class.ppt
 
STate Space Analysis
STate Space AnalysisSTate Space Analysis
STate Space Analysis
 
Chaos Suppression and Stabilization of Generalized Liu Chaotic Control System
Chaos Suppression and Stabilization of Generalized Liu Chaotic Control SystemChaos Suppression and Stabilization of Generalized Liu Chaotic Control System
Chaos Suppression and Stabilization of Generalized Liu Chaotic Control System
 
A novel approach for high speed convolution of finite
A novel approach for high speed convolution of finiteA novel approach for high speed convolution of finite
A novel approach for high speed convolution of finite
 
Section9 stochastic
Section9 stochasticSection9 stochastic
Section9 stochastic
 
Controllability of Linear Dynamical System
Controllability of  Linear Dynamical SystemControllability of  Linear Dynamical System
Controllability of Linear Dynamical System
 
Signal Processing Assignment Help
Signal Processing Assignment HelpSignal Processing Assignment Help
Signal Processing Assignment Help
 
A novel approach for high speed convolution of finite and infinite length seq...
A novel approach for high speed convolution of finite and infinite length seq...A novel approach for high speed convolution of finite and infinite length seq...
A novel approach for high speed convolution of finite and infinite length seq...
 
DSP_FOEHU - MATLAB 01 - Discrete Time Signals and Systems
DSP_FOEHU - MATLAB 01 - Discrete Time Signals and SystemsDSP_FOEHU - MATLAB 01 - Discrete Time Signals and Systems
DSP_FOEHU - MATLAB 01 - Discrete Time Signals and Systems
 
P73
P73P73
P73
 
1 Aminullah Assagaf_Estimation-of-domain-of-attraction-for-the-fract_2021_Non...
1 Aminullah Assagaf_Estimation-of-domain-of-attraction-for-the-fract_2021_Non...1 Aminullah Assagaf_Estimation-of-domain-of-attraction-for-the-fract_2021_Non...
1 Aminullah Assagaf_Estimation-of-domain-of-attraction-for-the-fract_2021_Non...
 
Simple Comparison of Convergence of GeneralIterations and Effect of Variation...
Simple Comparison of Convergence of GeneralIterations and Effect of Variation...Simple Comparison of Convergence of GeneralIterations and Effect of Variation...
Simple Comparison of Convergence of GeneralIterations and Effect of Variation...
 
Theoretical and Practical Bounds on the Initial Value of Skew-Compensated Clo...
Theoretical and Practical Bounds on the Initial Value of Skew-Compensated Clo...Theoretical and Practical Bounds on the Initial Value of Skew-Compensated Clo...
Theoretical and Practical Bounds on the Initial Value of Skew-Compensated Clo...
 

Recently uploaded

Call for Papers - African Journal of Biological Sciences, E-ISSN: 2663-2187, ...
Call for Papers - African Journal of Biological Sciences, E-ISSN: 2663-2187, ...Call for Papers - African Journal of Biological Sciences, E-ISSN: 2663-2187, ...
Call for Papers - African Journal of Biological Sciences, E-ISSN: 2663-2187, ...
Christo Ananth
 
Call for Papers - Educational Administration: Theory and Practice, E-ISSN: 21...
Call for Papers - Educational Administration: Theory and Practice, E-ISSN: 21...Call for Papers - Educational Administration: Theory and Practice, E-ISSN: 21...
Call for Papers - Educational Administration: Theory and Practice, E-ISSN: 21...
Christo Ananth
 
result management system report for college project
result management system report for college projectresult management system report for college project
result management system report for college project
Tonystark477637
 
AKTU Computer Networks notes --- Unit 3.pdf
AKTU Computer Networks notes ---  Unit 3.pdfAKTU Computer Networks notes ---  Unit 3.pdf
AKTU Computer Networks notes --- Unit 3.pdf
ankushspencer015
 

Recently uploaded (20)

Call for Papers - African Journal of Biological Sciences, E-ISSN: 2663-2187, ...
Call for Papers - African Journal of Biological Sciences, E-ISSN: 2663-2187, ...Call for Papers - African Journal of Biological Sciences, E-ISSN: 2663-2187, ...
Call for Papers - African Journal of Biological Sciences, E-ISSN: 2663-2187, ...
 
ONLINE FOOD ORDER SYSTEM PROJECT REPORT.pdf
ONLINE FOOD ORDER SYSTEM PROJECT REPORT.pdfONLINE FOOD ORDER SYSTEM PROJECT REPORT.pdf
ONLINE FOOD ORDER SYSTEM PROJECT REPORT.pdf
 
Porous Ceramics seminar and technical writing
Porous Ceramics seminar and technical writingPorous Ceramics seminar and technical writing
Porous Ceramics seminar and technical writing
 
Glass Ceramics: Processing and Properties
Glass Ceramics: Processing and PropertiesGlass Ceramics: Processing and Properties
Glass Ceramics: Processing and Properties
 
Call for Papers - Educational Administration: Theory and Practice, E-ISSN: 21...
Call for Papers - Educational Administration: Theory and Practice, E-ISSN: 21...Call for Papers - Educational Administration: Theory and Practice, E-ISSN: 21...
Call for Papers - Educational Administration: Theory and Practice, E-ISSN: 21...
 
Processing & Properties of Floor and Wall Tiles.pptx
Processing & Properties of Floor and Wall Tiles.pptxProcessing & Properties of Floor and Wall Tiles.pptx
Processing & Properties of Floor and Wall Tiles.pptx
 
(INDIRA) Call Girl Aurangabad Call Now 8617697112 Aurangabad Escorts 24x7
(INDIRA) Call Girl Aurangabad Call Now 8617697112 Aurangabad Escorts 24x7(INDIRA) Call Girl Aurangabad Call Now 8617697112 Aurangabad Escorts 24x7
(INDIRA) Call Girl Aurangabad Call Now 8617697112 Aurangabad Escorts 24x7
 
Extrusion Processes and Their Limitations
Extrusion Processes and Their LimitationsExtrusion Processes and Their Limitations
Extrusion Processes and Their Limitations
 
UNIT - IV - Air Compressors and its Performance
UNIT - IV - Air Compressors and its PerformanceUNIT - IV - Air Compressors and its Performance
UNIT - IV - Air Compressors and its Performance
 
(ANJALI) Dange Chowk Call Girls Just Call 7001035870 [ Cash on Delivery ] Pun...
(ANJALI) Dange Chowk Call Girls Just Call 7001035870 [ Cash on Delivery ] Pun...(ANJALI) Dange Chowk Call Girls Just Call 7001035870 [ Cash on Delivery ] Pun...
(ANJALI) Dange Chowk Call Girls Just Call 7001035870 [ Cash on Delivery ] Pun...
 
UNIT-III FMM. DIMENSIONAL ANALYSIS
UNIT-III FMM.        DIMENSIONAL ANALYSISUNIT-III FMM.        DIMENSIONAL ANALYSIS
UNIT-III FMM. DIMENSIONAL ANALYSIS
 
Sheet Pile Wall Design and Construction: A Practical Guide for Civil Engineer...
Sheet Pile Wall Design and Construction: A Practical Guide for Civil Engineer...Sheet Pile Wall Design and Construction: A Practical Guide for Civil Engineer...
Sheet Pile Wall Design and Construction: A Practical Guide for Civil Engineer...
 
result management system report for college project
result management system report for college projectresult management system report for college project
result management system report for college project
 
AKTU Computer Networks notes --- Unit 3.pdf
AKTU Computer Networks notes ---  Unit 3.pdfAKTU Computer Networks notes ---  Unit 3.pdf
AKTU Computer Networks notes --- Unit 3.pdf
 
Introduction and different types of Ethernet.pptx
Introduction and different types of Ethernet.pptxIntroduction and different types of Ethernet.pptx
Introduction and different types of Ethernet.pptx
 
(SHREYA) Chakan Call Girls Just Call 7001035870 [ Cash on Delivery ] Pune Esc...
(SHREYA) Chakan Call Girls Just Call 7001035870 [ Cash on Delivery ] Pune Esc...(SHREYA) Chakan Call Girls Just Call 7001035870 [ Cash on Delivery ] Pune Esc...
(SHREYA) Chakan Call Girls Just Call 7001035870 [ Cash on Delivery ] Pune Esc...
 
Booking open Available Pune Call Girls Koregaon Park 6297143586 Call Hot Ind...
Booking open Available Pune Call Girls Koregaon Park  6297143586 Call Hot Ind...Booking open Available Pune Call Girls Koregaon Park  6297143586 Call Hot Ind...
Booking open Available Pune Call Girls Koregaon Park 6297143586 Call Hot Ind...
 
High Profile Call Girls Nagpur Meera Call 7001035870 Meet With Nagpur Escorts
High Profile Call Girls Nagpur Meera Call 7001035870 Meet With Nagpur EscortsHigh Profile Call Girls Nagpur Meera Call 7001035870 Meet With Nagpur Escorts
High Profile Call Girls Nagpur Meera Call 7001035870 Meet With Nagpur Escorts
 
Water Industry Process Automation & Control Monthly - April 2024
Water Industry Process Automation & Control Monthly - April 2024Water Industry Process Automation & Control Monthly - April 2024
Water Industry Process Automation & Control Monthly - April 2024
 
Call Girls Pimpri Chinchwad Call Me 7737669865 Budget Friendly No Advance Boo...
Call Girls Pimpri Chinchwad Call Me 7737669865 Budget Friendly No Advance Boo...Call Girls Pimpri Chinchwad Call Me 7737669865 Budget Friendly No Advance Boo...
Call Girls Pimpri Chinchwad Call Me 7737669865 Budget Friendly No Advance Boo...
 

DSP Lec 1.ppt

  • 1. 1 Digital Signal Processing (DSP) Lecture no 1 Discrete-Time Signals and Systems
  • 5.
  • 14. 14 Sum of two sequences Product of two sequences Multiplication of a sequence by a numberα Delay (shift) of a sequence Basic Sequence Operations ] [ ] [ n y n x  integer : ] [ ] [ 0 0 n n n x n y   14 ] [ ] [ n y n x  ] [n x  
  • 15. 15 Basic sequences Unit sample sequence (discrete-time impulse, impulse)         0 1 0 0 n n n  7/6/2023 15
  • 16. 16 Basic sequences Unit step sequence       0 0 0 1 ] [ n n n u 7/6/2023 16       n k k n u  ] [            0 ] [ ] 2 [ ] 1 [ ] [ ] [ k k n n n n n u      ] 1 [ ] [ ] [    n u n u n  First backward difference       0, 0 , 1, 0 0 0 1 0 since n k when n k when n k k k                    
  • 17. 17 Basic Sequences Exponential sequences n A n x   ] [ 7/6/2023 17 A and α are real: x[n] is real A is positive and 0<α<1, x[n] is positive and decrease with increasing n -1<α<0, x[n] alternate in sign, but decrease in magnitude with increasing n  : x[n] grows in magnitude as n increases 1  
  • 18. 18 EX. 1 Combining Basic sequences       0 0 0 ] [ n n A n x n  7/6/2023 18 If we want an exponential sequences that is zero for n <0, then ] [ ] [ n u A n x n   Cumbersome simpler
  • 19. 19 Periodic Sequences A periodic sequence with integer period N n all for N n x n x ] [ ] [             N w n w A n w A 0 0 0 cos cos 7/6/2023 19 integer , 2 0 is k where k N w   0 2 / , integer N k w where k is  
  • 21. 21 Discrete-Time System Discrete-Time System is a trasformation or operator that maps input sequence x[n] into a unique y[n] y[n]=T{x[n]}, x[n], y[n]: discrete-time signal 7/6/2023 21 T{‧} x[n] y[n] Discrete-Time System
  • 22. 22 EX. 5 The Ideal Delay System        n n n x n y d ], [ ] [ 7/6/2023 22 If is a positive integer: the delay of the system. Shift the input sequence to the right by samples to form the output . d n d n If is a negative integer: the system will shift the input to the left by samples, corresponding to a time advance. d n d n
  • 23. 23 Properties of Discrete-time systems Memoryless (memory) system
  • 24. 24 Properties of Discrete-time systems Linear Systems 7/6/2023 24  If   n y1 T{‧}   n x1   n y2   n x2 T{‧}   n ay   n ax T{‧}       n bx n ax n x 2 1 3         n by n ay n y 2 1 3   T{‧}     n y n y 2 1      n x n x 2 1  T{‧} additivity property homogeneity or scaling property  principle of superposition  and only If:
  • 25. 25 Example Nonlinear Systems 7/6/2023 25 Method: find one counterexample  2 2 2 1 1 1 1     counterexample    2 ] [n x n y   For     ] [ log10 n x n y      1 10 log 1 log 10 10 10     counterexample  For
  • 26. 26 Properties of Discrete-time systems Time-Invariant Systems Shift-Invariant Systems 7/6/2023 26     0 1 2 n n x n x       0 1 2 n n y n y     n y1 T{‧}   n x1 T{‧}
  • 27.
  • 28. 28
  • 29. 29 Properties of Discrete-time systems Causality A system is causal if, for every choice of , the output sequence value at the index depends only on the input sequence value for 0 n 0 n n  7/6/2023 29 0 n n 
  • 30. 30 Ex:9 Example for Causal System Forward difference system is not Causal Backward difference system is Causal       n x n x n y    1       1    n x n x n y 7/6/2023 30
  • 31.
  • 32. 32 Properties of Discrete-time system Stability Bounded-Input Bounded-Output (BIBO) Stability: every bounded input sequence produces a bounded output sequence.   n all for B n x x ,      n all for B n y y ,    7/6/2023 32 if then
  • 33. 33 Ex:10 Test for Stability or Instability    2 ] [n x n y    n all for B n x x ,      n all for B B n y x y , 2     7/6/2023 33 if then is stable
  • 34. 34 Accumulator system         n k k x n y     bounded n n n u n x : 0 1 0 0        Ex:11 Test for Stability or Instability 7/6/2023 34                      bounded not n n n k x k x n y n k n k : 0 1 0 0 Accumulator system is not stable
  • 35. 35 Linear Time-Invariant (LTI) Systems Impulse response 7/6/2023 35   0 n n     n h   n    0 n n h  T{‧} T{‧}
  • 36. 36 LTI Systems: Convolution             k k n k x n x                                                k k k n h n x k n h k x k n T k x k n k x T n y   7/6/2023 36 Representation of general sequence as a linear combination of delayed impulse principle of superposition An Illustration Example(interpretation 1)
  • 37.
  • 38. 38 Properties of LTI Systems Convolution is commutative         n x n h n h n x    7/6/2023 38 h[n] x[n] y[n] x[n] h[n] y[n]                 n h n x n h n x n h n h n x 2 1 2 1       Convolution is distributed over addition
  • 39. 39 Cascade connection of systems       n h n h n h 2 1   7/6/2023 39 x [n] h1[n] h2[n] y [n] x [n] h2[n] h1[n] y [n] x [n] h1[n] ]h2[n] y [n]
  • 40. 40 Parallel connection of systems       n h n h n h 2 1   7/6/2023 40
  • 41. 41 Stability of LTI Systems LTI system is stable if the impulse response is absolutely summable .          k k h S 41 Causality of LTI systems   0 , 0   n n h HW: proof, Problem 2.62
  • 42. End chapter problems 1.1, 1.2,  Example 2.33, 2.6a, 2. 7, 2.17 a b, 42