SlideShare a Scribd company logo
A Presentation on Basics of
Signal & Systems
By:-
Sunil Kumar Yadav (2013UEE1176)
Pawan Kumar Jangid (2013UEE1166)
Manish Kumar Bagara (2013UEE1180)
Chandan Kumar (2013UEE1203)
Subject:- Network, Signal & Systems
What is a Signal?
• A signal is a pattern of variation of some form
• Signals are variables that carry information
Examples of signal include:
Electrical signals
– Voltages and currents in a circuit
Acoustic signals
– Acoustic pressure (sound) over time
Mechanical signals
– Velocity of a car over time
Video signals
– Intensity level of a pixel (camera, video) over time
How is a Signal Represented?
Mathematically, signals are represented as a function of
one or more independent variables.
For instance a black & white video signal intensity is
dependent on x, y coordinates and time t f(x,y,t)
On this course, we shall be exclusively concerned with
signals that are a function of a single variable: time
t
f(t)
Example: Signals in an Electrical Circuit
The signals vc and vs are patterns of variation over time
Note, we could also have considered the voltage across the resistor or
the current as signals
+
-
i vcvs
R
C
)(
1
)(
1)(
)(
)(
)()(
)(
tv
RC
tv
RCdt
tdv
dt
tdv
Cti
R
tvtv
ti
sc
c
c
cs
=+
=
−
=
• Step (signal) vs at t=1
• RC = 1
• First order (exponential)
response for vc
vs,vc
t
Continuous & Discrete-Time Signals
Continuous-Time Signals
Most signals in the real world are
continuous time, as the scale is
infinitesimally fine.
Eg voltage, velocity,
Denote by x(t), where the time
interval may be bounded (finite) or
infinite
Discrete-Time Signals
Some real world and many digital
signals are discrete time, as they
are sampled
E.g. pixels, daily stock price
(anything that a digital computer
processes)
Denote by x[n], where n is an integer
value that varies discretely
Sampled continuous signal
x[n] =x(nk) – k is sample time
x(t)
t
x[n]
n
Signal Properties
On this course, we shall be particularly interested in signals with
certain properties:
Periodic signals: a signal is periodic if it repeats itself after a fixed
period T, i.e. x(t) = x(t+T) for all t. A sin(t) signal is periodic.
Even and odd signals: a signal is even if x(-t) = x(t) (i.e. it can be
reflected in the axis at zero). A signal is odd if x(-t) = -x(t).
Examples are cos(t) and sin(t) signals, respectively.
Exponential and sinusoidal signals: a signal is (real) exponential if it
can be represented as x(t) = Ceat
. A signal is (complex) exponential
if it can be represented in the same form but C and a are complex
numbers.
Step and pulse signals: A pulse signal is one which is nearly
completely zero, apart from a short spike, δ(t). A step signal is zero
up to a certain time, and then a constant value after that time, u(t).
These properties define a large class of tractable, useful signals and
will be further considered in the coming lectures
What is a System?
• Systems process input signals to produce output
signals
Examples:
– A circuit involving a capacitor can be viewed as a
system that transforms the source voltage (signal) to
the voltage (signal) across the capacitor
– A CD player takes the signal on the CD and transforms
it into a signal sent to the loud speaker
– A communication system is generally composed of
three sub-systems, the transmitter, the channel and the
receiver. The channel typically attenuates and adds
noise to the transmitted signal which must be
processed by the receiver
How is a System Represented?
A system takes a signal as an input and transforms it
into another signal
In a very broad sense, a system can be represented as
the ratio of the output signal over the input signal
That way, when we “multiply” the system by the input
signal, we get the output signal
This concept will be firmed up in the coming weeks
System
Input signal
x(t)
Output signal
y(t)
Example: An Electrical Circuit System
Simulink representation of the electrical circuit
+
-
i vcvs
R
C
)(
1
)(
1)(
)(
)(
)()(
)(
tv
RC
tv
RCdt
tdv
dt
tdv
Cti
R
tvtv
ti
sc
c
c
cs
=+
=
−
=
vs(t) vc(t)
first order
system
vs,vc
t
Continuous & Discrete-Time
Mathematical Models of Systems
Continuous-Time Systems
Most continuous time systems
represent how continuous
signals are transformed via
differential equations.
E.g. circuit, car velocity
Discrete-Time Systems
Most discrete time systems
represent how discrete signals
are transformed via difference
equations
E.g. bank account, discrete car
velocity system
)(
1
)(
1)(
tv
RC
tv
RCdt
tdv
sc
c
=+
)()(
)(
tftv
dt
tdv
m =+ ρ
First order differential equations
][]1[01.1][ nxnyny +−=
][]1[][ nf
m
nv
m
m
nv
∆+
∆
=−
∆+
−
ρρ
First order difference equations
∆
∆−−∆
=
∆ ))1(()()( nvnv
dt
ndv
Properties of a System
On this course, we shall be particularly interested in
signals with certain properties:
• Causal: a system is causal if the output at a time, only
depends on input values up to that time.
• Linear: a system is linear if the output of the scaled
sum of two input signals is the equivalent scaled sum of
outputs
• Time-invariance: a system is time invariant if the
system’s output is the same, given the same input
signal, regardless of time.
These properties define a large class of tractable, useful
systems and will be further considered in the coming
lectures
Thank You

More Related Content

What's hot

Comparsion of M-Ary psk,fsk,qapsk.pptx
Comparsion of M-Ary psk,fsk,qapsk.pptxComparsion of M-Ary psk,fsk,qapsk.pptx
Comparsion of M-Ary psk,fsk,qapsk.pptx
keshav11845
 
Analog communication
Analog communicationAnalog communication
Analog communication
Preston King
 
Noise in communication system
Noise in communication systemNoise in communication system
Noise in communication system
firdous006
 

What's hot (20)

Signals & Systems PPT
Signals & Systems PPTSignals & Systems PPT
Signals & Systems PPT
 
Solved problems
Solved problemsSolved problems
Solved problems
 
Am transmitter
Am transmitterAm transmitter
Am transmitter
 
Lecture 4: Classification of system
Lecture 4: Classification of system Lecture 4: Classification of system
Lecture 4: Classification of system
 
IIR filter realization using direct form I & II
IIR filter realization using direct form I & IIIIR filter realization using direct form I & II
IIR filter realization using direct form I & II
 
MOSFETs
MOSFETsMOSFETs
MOSFETs
 
Signals & systems
Signals & systems Signals & systems
Signals & systems
 
Noise
NoiseNoise
Noise
 
Discrete Time Systems & its classifications
Discrete Time Systems & its classificationsDiscrete Time Systems & its classifications
Discrete Time Systems & its classifications
 
Transmission lines
Transmission linesTransmission lines
Transmission lines
 
Comparsion of M-Ary psk,fsk,qapsk.pptx
Comparsion of M-Ary psk,fsk,qapsk.pptxComparsion of M-Ary psk,fsk,qapsk.pptx
Comparsion of M-Ary psk,fsk,qapsk.pptx
 
Cascaded differential amplifier
Cascaded differential amplifierCascaded differential amplifier
Cascaded differential amplifier
 
Analog communication
Analog communicationAnalog communication
Analog communication
 
Digital signal System
Digital signal SystemDigital signal System
Digital signal System
 
Noise in communication system
Noise in communication systemNoise in communication system
Noise in communication system
 
Digital Communication: Information Theory
Digital Communication: Information TheoryDigital Communication: Information Theory
Digital Communication: Information Theory
 
Line coding
Line codingLine coding
Line coding
 
Amplifier frequency response(part 1)
Amplifier frequency response(part 1)Amplifier frequency response(part 1)
Amplifier frequency response(part 1)
 
Op amp
Op ampOp amp
Op amp
 
Bjt amplifiers
Bjt amplifiersBjt amplifiers
Bjt amplifiers
 

Viewers also liked

Dr hoppe arrythmias
Dr hoppe arrythmiasDr hoppe arrythmias
Dr hoppe arrythmias
guest68d38f
 
Aplicaciones de las series de fourier
Aplicaciones de las series de fourierAplicaciones de las series de fourier
Aplicaciones de las series de fourier
Pedro Guerrero
 

Viewers also liked (20)

2. signal & systems beyonds
2. signal & systems  beyonds2. signal & systems  beyonds
2. signal & systems beyonds
 
Signal & systems
Signal & systemsSignal & systems
Signal & systems
 
Basics of signals data communication
Basics of signals data communicationBasics of signals data communication
Basics of signals data communication
 
Lecture3 Signal and Systems
Lecture3 Signal and SystemsLecture3 Signal and Systems
Lecture3 Signal and Systems
 
Manipulation of light in the Nano world , Laser Traffic Light , IDM9
Manipulation of light in the Nano world , Laser Traffic Light , IDM9Manipulation of light in the Nano world , Laser Traffic Light , IDM9
Manipulation of light in the Nano world , Laser Traffic Light , IDM9
 
2nd Annual Arrhythmia and Heart Failure Symposium
2nd Annual Arrhythmia and Heart Failure Symposium2nd Annual Arrhythmia and Heart Failure Symposium
2nd Annual Arrhythmia and Heart Failure Symposium
 
Symposium of Integrated Mapping Tool for Cardiac Arrhythmia
Symposium of Integrated Mapping Tool for Cardiac ArrhythmiaSymposium of Integrated Mapping Tool for Cardiac Arrhythmia
Symposium of Integrated Mapping Tool for Cardiac Arrhythmia
 
Dr hoppe arrythmias
Dr hoppe arrythmiasDr hoppe arrythmias
Dr hoppe arrythmias
 
Dr Vanita Arora - Arrhythmia Diagnosis in India
Dr Vanita Arora - Arrhythmia Diagnosis in IndiaDr Vanita Arora - Arrhythmia Diagnosis in India
Dr Vanita Arora - Arrhythmia Diagnosis in India
 
Aplicaciones de las series de fourier
Aplicaciones de las series de fourierAplicaciones de las series de fourier
Aplicaciones de las series de fourier
 
Communication systems notes - Akshansh
Communication systems notes - AkshanshCommunication systems notes - Akshansh
Communication systems notes - Akshansh
 
Hair Boom (Hair Bang) Product Introduction - Laser Helmet for Hair Loss
Hair Boom (Hair Bang) Product Introduction - Laser Helmet for Hair LossHair Boom (Hair Bang) Product Introduction - Laser Helmet for Hair Loss
Hair Boom (Hair Bang) Product Introduction - Laser Helmet for Hair Loss
 
Biology Notes - Akshansh
Biology Notes - AkshanshBiology Notes - Akshansh
Biology Notes - Akshansh
 
Advanced Mathematics
Advanced MathematicsAdvanced Mathematics
Advanced Mathematics
 
Communication Networks Notes - Akshansh
Communication Networks Notes - AkshanshCommunication Networks Notes - Akshansh
Communication Networks Notes - Akshansh
 
Number theory Notes - Akshansh
Number theory  Notes - AkshanshNumber theory  Notes - Akshansh
Number theory Notes - Akshansh
 
MEMS Notes - Akshansh
MEMS Notes - AkshanshMEMS Notes - Akshansh
MEMS Notes - Akshansh
 
signals and systems
signals and systemssignals and systems
signals and systems
 
Ecg
EcgEcg
Ecg
 
Heart Arrhythmia
Heart Arrhythmia Heart Arrhythmia
Heart Arrhythmia
 

Similar to 1. signal and systems basics

Lecture1 Intro To Signa
Lecture1 Intro To SignaLecture1 Intro To Signa
Lecture1 Intro To Signa
babak danyal
 
1.Basics of Signals
1.Basics of Signals1.Basics of Signals
1.Basics of Signals
INDIAN NAVY
 
Signals and classification
Signals and classificationSignals and classification
Signals and classification
Suraj Mishra
 
Signals and systems( chapter 1)
Signals and systems( chapter 1)Signals and systems( chapter 1)
Signals and systems( chapter 1)
Fariza Zahari
 

Similar to 1. signal and systems basics (20)

Lecture1 Intro To Signa
Lecture1 Intro To SignaLecture1 Intro To Signa
Lecture1 Intro To Signa
 
Bsa ppt 48
Bsa ppt 48Bsa ppt 48
Bsa ppt 48
 
Signals and System
Signals and SystemSignals and System
Signals and System
 
1.Basics of Signals
1.Basics of Signals1.Basics of Signals
1.Basics of Signals
 
Signals and system
Signals and systemSignals and system
Signals and system
 
Lecture 1
Lecture 1Lecture 1
Lecture 1
 
Signals basics
Signals basicsSignals basics
Signals basics
 
Signals and classification
Signals and classificationSignals and classification
Signals and classification
 
ssppt-170414031953.pdf
ssppt-170414031953.pdfssppt-170414031953.pdf
ssppt-170414031953.pdf
 
Signals and systems( chapter 1)
Signals and systems( chapter 1)Signals and systems( chapter 1)
Signals and systems( chapter 1)
 
02_signals.pdf
02_signals.pdf02_signals.pdf
02_signals.pdf
 
ssppt-170414031953.pptx
ssppt-170414031953.pptxssppt-170414031953.pptx
ssppt-170414031953.pptx
 
Classification of signal
Classification of signalClassification of signal
Classification of signal
 
10800120085.pdf
10800120085.pdf10800120085.pdf
10800120085.pdf
 
Signal & System Assignment
Signal & System Assignment Signal & System Assignment
Signal & System Assignment
 
Digital signal processing by YEASIN NEWAJ
Digital signal processing by YEASIN NEWAJDigital signal processing by YEASIN NEWAJ
Digital signal processing by YEASIN NEWAJ
 
3.Properties of signals
3.Properties of signals3.Properties of signals
3.Properties of signals
 
LECTURES summary .ppt
LECTURES summary .pptLECTURES summary .ppt
LECTURES summary .ppt
 
Introduction to signals and systems
Introduction to signals and systemsIntroduction to signals and systems
Introduction to signals and systems
 
Sns slide 1 2011
Sns slide 1 2011Sns slide 1 2011
Sns slide 1 2011
 

More from skysunilyadav (9)

Ecm sky
Ecm skyEcm sky
Ecm sky
 
Report
ReportReport
Report
 
Report
ReportReport
Report
 
My training
My trainingMy training
My training
 
Spectrum analyzer
Spectrum  analyzerSpectrum  analyzer
Spectrum analyzer
 
Coding Scheme/ Information theory/ Error coding scheme
Coding Scheme/ Information theory/ Error coding schemeCoding Scheme/ Information theory/ Error coding scheme
Coding Scheme/ Information theory/ Error coding scheme
 
5. fourier properties
5. fourier properties5. fourier properties
5. fourier properties
 
4. cft
4. cft4. cft
4. cft
 
3. convolution fourier
3. convolution fourier3. convolution fourier
3. convolution fourier
 

Recently uploaded

Standard Reomte Control Interface - Neometrix
Standard Reomte Control Interface - NeometrixStandard Reomte Control Interface - Neometrix
Standard Reomte Control Interface - Neometrix
Neometrix_Engineering_Pvt_Ltd
 
LIGA(E)11111111111111111111111111111111111111111.ppt
LIGA(E)11111111111111111111111111111111111111111.pptLIGA(E)11111111111111111111111111111111111111111.ppt
LIGA(E)11111111111111111111111111111111111111111.ppt
ssuser9bd3ba
 
Hall booking system project report .pdf
Hall booking system project report  .pdfHall booking system project report  .pdf
Hall booking system project report .pdf
Kamal Acharya
 
Online blood donation management system project.pdf
Online blood donation management system project.pdfOnline blood donation management system project.pdf
Online blood donation management system project.pdf
Kamal Acharya
 
RS Khurmi Machine Design Clutch and Brake Exercise Numerical Solutions
RS Khurmi Machine Design Clutch and Brake Exercise Numerical SolutionsRS Khurmi Machine Design Clutch and Brake Exercise Numerical Solutions
RS Khurmi Machine Design Clutch and Brake Exercise Numerical Solutions
Atif Razi
 
Automobile Management System Project Report.pdf
Automobile Management System Project Report.pdfAutomobile Management System Project Report.pdf
Automobile Management System Project Report.pdf
Kamal Acharya
 

Recently uploaded (20)

Scaling in conventional MOSFET for constant electric field and constant voltage
Scaling in conventional MOSFET for constant electric field and constant voltageScaling in conventional MOSFET for constant electric field and constant voltage
Scaling in conventional MOSFET for constant electric field and constant voltage
 
shape functions of 1D and 2 D rectangular elements.pptx
shape functions of 1D and 2 D rectangular elements.pptxshape functions of 1D and 2 D rectangular elements.pptx
shape functions of 1D and 2 D rectangular elements.pptx
 
Quality defects in TMT Bars, Possible causes and Potential Solutions.
Quality defects in TMT Bars, Possible causes and Potential Solutions.Quality defects in TMT Bars, Possible causes and Potential Solutions.
Quality defects in TMT Bars, Possible causes and Potential Solutions.
 
Explosives Industry manufacturing process.pdf
Explosives Industry manufacturing process.pdfExplosives Industry manufacturing process.pdf
Explosives Industry manufacturing process.pdf
 
ENERGY STORAGE DEVICES INTRODUCTION UNIT-I
ENERGY STORAGE DEVICES  INTRODUCTION UNIT-IENERGY STORAGE DEVICES  INTRODUCTION UNIT-I
ENERGY STORAGE DEVICES INTRODUCTION UNIT-I
 
WATER CRISIS and its solutions-pptx 1234
WATER CRISIS and its solutions-pptx 1234WATER CRISIS and its solutions-pptx 1234
WATER CRISIS and its solutions-pptx 1234
 
Standard Reomte Control Interface - Neometrix
Standard Reomte Control Interface - NeometrixStandard Reomte Control Interface - Neometrix
Standard Reomte Control Interface - Neometrix
 
Danfoss NeoCharge Technology -A Revolution in 2024.pdf
Danfoss NeoCharge Technology -A Revolution in 2024.pdfDanfoss NeoCharge Technology -A Revolution in 2024.pdf
Danfoss NeoCharge Technology -A Revolution in 2024.pdf
 
LIGA(E)11111111111111111111111111111111111111111.ppt
LIGA(E)11111111111111111111111111111111111111111.pptLIGA(E)11111111111111111111111111111111111111111.ppt
LIGA(E)11111111111111111111111111111111111111111.ppt
 
İTÜ CAD and Reverse Engineering Workshop
İTÜ CAD and Reverse Engineering WorkshopİTÜ CAD and Reverse Engineering Workshop
İTÜ CAD and Reverse Engineering Workshop
 
A CASE STUDY ON ONLINE TICKET BOOKING SYSTEM PROJECT.pdf
A CASE STUDY ON ONLINE TICKET BOOKING SYSTEM PROJECT.pdfA CASE STUDY ON ONLINE TICKET BOOKING SYSTEM PROJECT.pdf
A CASE STUDY ON ONLINE TICKET BOOKING SYSTEM PROJECT.pdf
 
Hall booking system project report .pdf
Hall booking system project report  .pdfHall booking system project report  .pdf
Hall booking system project report .pdf
 
Online blood donation management system project.pdf
Online blood donation management system project.pdfOnline blood donation management system project.pdf
Online blood donation management system project.pdf
 
RS Khurmi Machine Design Clutch and Brake Exercise Numerical Solutions
RS Khurmi Machine Design Clutch and Brake Exercise Numerical SolutionsRS Khurmi Machine Design Clutch and Brake Exercise Numerical Solutions
RS Khurmi Machine Design Clutch and Brake Exercise Numerical Solutions
 
Final project report on grocery store management system..pdf
Final project report on grocery store management system..pdfFinal project report on grocery store management system..pdf
Final project report on grocery store management system..pdf
 
HYDROPOWER - Hydroelectric power generation
HYDROPOWER - Hydroelectric power generationHYDROPOWER - Hydroelectric power generation
HYDROPOWER - Hydroelectric power generation
 
The Benefits and Techniques of Trenchless Pipe Repair.pdf
The Benefits and Techniques of Trenchless Pipe Repair.pdfThe Benefits and Techniques of Trenchless Pipe Repair.pdf
The Benefits and Techniques of Trenchless Pipe Repair.pdf
 
Event Management System Vb Net Project Report.pdf
Event Management System Vb Net  Project Report.pdfEvent Management System Vb Net  Project Report.pdf
Event Management System Vb Net Project Report.pdf
 
Automobile Management System Project Report.pdf
Automobile Management System Project Report.pdfAutomobile Management System Project Report.pdf
Automobile Management System Project Report.pdf
 
Arduino based vehicle speed tracker project
Arduino based vehicle speed tracker projectArduino based vehicle speed tracker project
Arduino based vehicle speed tracker project
 

1. signal and systems basics

  • 1. A Presentation on Basics of Signal & Systems By:- Sunil Kumar Yadav (2013UEE1176) Pawan Kumar Jangid (2013UEE1166) Manish Kumar Bagara (2013UEE1180) Chandan Kumar (2013UEE1203) Subject:- Network, Signal & Systems
  • 2. What is a Signal? • A signal is a pattern of variation of some form • Signals are variables that carry information Examples of signal include: Electrical signals – Voltages and currents in a circuit Acoustic signals – Acoustic pressure (sound) over time Mechanical signals – Velocity of a car over time Video signals – Intensity level of a pixel (camera, video) over time
  • 3. How is a Signal Represented? Mathematically, signals are represented as a function of one or more independent variables. For instance a black & white video signal intensity is dependent on x, y coordinates and time t f(x,y,t) On this course, we shall be exclusively concerned with signals that are a function of a single variable: time t f(t)
  • 4. Example: Signals in an Electrical Circuit The signals vc and vs are patterns of variation over time Note, we could also have considered the voltage across the resistor or the current as signals + - i vcvs R C )( 1 )( 1)( )( )( )()( )( tv RC tv RCdt tdv dt tdv Cti R tvtv ti sc c c cs =+ = − = • Step (signal) vs at t=1 • RC = 1 • First order (exponential) response for vc vs,vc t
  • 5. Continuous & Discrete-Time Signals Continuous-Time Signals Most signals in the real world are continuous time, as the scale is infinitesimally fine. Eg voltage, velocity, Denote by x(t), where the time interval may be bounded (finite) or infinite Discrete-Time Signals Some real world and many digital signals are discrete time, as they are sampled E.g. pixels, daily stock price (anything that a digital computer processes) Denote by x[n], where n is an integer value that varies discretely Sampled continuous signal x[n] =x(nk) – k is sample time x(t) t x[n] n
  • 6. Signal Properties On this course, we shall be particularly interested in signals with certain properties: Periodic signals: a signal is periodic if it repeats itself after a fixed period T, i.e. x(t) = x(t+T) for all t. A sin(t) signal is periodic. Even and odd signals: a signal is even if x(-t) = x(t) (i.e. it can be reflected in the axis at zero). A signal is odd if x(-t) = -x(t). Examples are cos(t) and sin(t) signals, respectively. Exponential and sinusoidal signals: a signal is (real) exponential if it can be represented as x(t) = Ceat . A signal is (complex) exponential if it can be represented in the same form but C and a are complex numbers. Step and pulse signals: A pulse signal is one which is nearly completely zero, apart from a short spike, δ(t). A step signal is zero up to a certain time, and then a constant value after that time, u(t). These properties define a large class of tractable, useful signals and will be further considered in the coming lectures
  • 7. What is a System? • Systems process input signals to produce output signals Examples: – A circuit involving a capacitor can be viewed as a system that transforms the source voltage (signal) to the voltage (signal) across the capacitor – A CD player takes the signal on the CD and transforms it into a signal sent to the loud speaker – A communication system is generally composed of three sub-systems, the transmitter, the channel and the receiver. The channel typically attenuates and adds noise to the transmitted signal which must be processed by the receiver
  • 8. How is a System Represented? A system takes a signal as an input and transforms it into another signal In a very broad sense, a system can be represented as the ratio of the output signal over the input signal That way, when we “multiply” the system by the input signal, we get the output signal This concept will be firmed up in the coming weeks System Input signal x(t) Output signal y(t)
  • 9. Example: An Electrical Circuit System Simulink representation of the electrical circuit + - i vcvs R C )( 1 )( 1)( )( )( )()( )( tv RC tv RCdt tdv dt tdv Cti R tvtv ti sc c c cs =+ = − = vs(t) vc(t) first order system vs,vc t
  • 10. Continuous & Discrete-Time Mathematical Models of Systems Continuous-Time Systems Most continuous time systems represent how continuous signals are transformed via differential equations. E.g. circuit, car velocity Discrete-Time Systems Most discrete time systems represent how discrete signals are transformed via difference equations E.g. bank account, discrete car velocity system )( 1 )( 1)( tv RC tv RCdt tdv sc c =+ )()( )( tftv dt tdv m =+ ρ First order differential equations ][]1[01.1][ nxnyny +−= ][]1[][ nf m nv m m nv ∆+ ∆ =− ∆+ − ρρ First order difference equations ∆ ∆−−∆ = ∆ ))1(()()( nvnv dt ndv
  • 11. Properties of a System On this course, we shall be particularly interested in signals with certain properties: • Causal: a system is causal if the output at a time, only depends on input values up to that time. • Linear: a system is linear if the output of the scaled sum of two input signals is the equivalent scaled sum of outputs • Time-invariance: a system is time invariant if the system’s output is the same, given the same input signal, regardless of time. These properties define a large class of tractable, useful systems and will be further considered in the coming lectures