Sampling theorem

Shanu Bhuvana
Shanu BhuvanaStudying em Student
• Presented by.,
• S.Shanmathee
Sampling Theorem
2/6/2015
ADC
• Generally signals are analog in nature (eg:speech,weather
signals).
• To process the analog signal by digital means, it is essential
to convert them to discrete-time signal , and then convert
them to a sequence of numbers.
• The process of converting an analog to digital signal is
‘Analog-to-Digital Conversion’.
• The ADC involves three steps which are:
1)Sampling
2)Quantization
3)coding
2/6/2015
• Analog signals: continuous in time and amplitude
– Example: voltage, current, temperature,…
• Digital signals: discrete both in time and amplitude
– Example: attendance of this class, digitizes analog
signals,…
• Discrete-time signal: discrete in time, continuous in
amplitude
– Example: hourly change of temperature in Austin
TYPES OF SIGNALS
2/6/2015
• During sampling process, a continuous-time signal is
converted into discrete -time signals by taking samples
of continuous-time signal at discrete time intervals.
)()( txnTsx 
T=Sampling Interval
x (t)=Analog input signal
2/6/2015
•Sampling theorem gives the criteria for minimum number
of samples that should be taken.
•Sampling criteria:-”Sampling frequency must be
twice of the highest frequency”
fs=2W
fs=sampling frequency
w=higher frequency content
2w also known as Nyquist rate
2/6/2015
•Nyquist rate is defined as the minimum sampling rate for the
perfect reconstruction of the continuous time signals from
samples.
•Nyquist rate=2*highest frequency component
=2*W
•So sampling rate must be greater than or equal to nyquist rate
2/6/2015
•There are two parts,
representation of x(t) in its samples
reconstruction of x(t)
Representation of x(t) in its samples
1.Define x∂(t)
2.Take fourier transform of x∂(t)) (i.e) x∂(f)
3.Relation between x(f) and x∂(f)
4.Relation between x(t) and x(nTs)
2/6/2015
Reconstruction of x(t)
1.Take inverse fourier transform of x∂(f)
2.Show that x(t) is obtained back with the help of
interpolation function
2/6/2015
•While providing sampling theorem we considered fs=2W
•Consider the case that fs < 2W
2/6/2015
Effects of Aliasing,
1.Distortion.
2.The data is lost and it cannot be recovered.
To avoid Aliasing,
1.sampling rate must be fs>=2W.
2.strictly bandlimit the signal to ’W’.
2/6/2015
2/6/2015
In general form, any continuous signal can be written as
S(t)=A1 cos(jw1t)+ A2 cos(jw2t)+ A3 cos(jw3t)
F1= w1/2∏ = 50∏/2∏ = 25HZ
F2= w2/2∏ = 300∏/2∏ = 150HZ
F3= w3/2∏ = 100∏/2∏ = 50HZ
Here, highest frequency component=150HZ
Hence Nyquist rate=2*150HZ=300HZ
)100cos(10)300sin(20)50cos(5)( tttts 
2/6/2015
•What is the minimum sampling rate(nyquist rate)?
Highest frequency=100HZ
So, Nyquist rate=2W=2*100=200HZ
•If sampling frequency is 400HZ then what is the discrete
time signal obtained?
f=freq of continuous signal/sampling freq
=100/400=1/4
Discrete time signal=5 cos(2∏fn)=5 cos (2∏*1/4 n)
=5 cos(∏n/2)
)200cos(5)( tts 
2/6/2015
2/6/2015
“SIGNALS AND SYSTEMS”
by Dr.J.S.Chitode
Optimist: "The glass is
half full."
Pessimist: "The glass is
half empty."
Engineer: "That glass is
twice as large as it
needs to be."
2/6/2015
1 de 16

Recomendados

Sampling Theorem por
Sampling TheoremSampling Theorem
Sampling TheoremDr Naim R Kidwai
5.5K visualizações19 slides
Sampling por
SamplingSampling
SamplingMuhammad Uzair Rasheed
13.3K visualizações34 slides
3.Frequency Domain Representation of Signals and Systems por
3.Frequency Domain Representation of Signals and Systems3.Frequency Domain Representation of Signals and Systems
3.Frequency Domain Representation of Signals and SystemsINDIAN NAVY
2.3K visualizações31 slides
Amplitude Modulation ppt por
Amplitude Modulation pptAmplitude Modulation ppt
Amplitude Modulation pptPriyanka Mathur
84.6K visualizações18 slides
Delta modulation por
Delta modulationDelta modulation
Delta modulationmpsrekha83
1.3K visualizações21 slides
Solved problems in waveguides por
Solved problems in waveguidesSolved problems in waveguides
Solved problems in waveguidessubhashinivec
6.2K visualizações54 slides

Mais conteúdo relacionado

Mais procurados

Signal classification of signal por
Signal classification of signalSignal classification of signal
Signal classification of signal001Abhishek1
9.9K visualizações22 slides
Digital modulation techniques... por
Digital modulation techniques...Digital modulation techniques...
Digital modulation techniques...Nidhi Baranwal
23.6K visualizações18 slides
M ary psk modulation por
M ary psk modulationM ary psk modulation
M ary psk modulationAhmed Diaa
37.8K visualizações12 slides
DPCM por
DPCMDPCM
DPCMsuryateja swamy
28.2K visualizações23 slides
Signals & Systems PPT por
Signals & Systems PPTSignals & Systems PPT
Signals & Systems PPTJay Baria
61K visualizações36 slides
quantization por
quantizationquantization
quantizationaniruddh Tyagi
21.6K visualizações33 slides

Mais procurados(20)

Signal classification of signal por 001Abhishek1
Signal classification of signalSignal classification of signal
Signal classification of signal
001Abhishek19.9K visualizações
Digital modulation techniques... por Nidhi Baranwal
Digital modulation techniques...Digital modulation techniques...
Digital modulation techniques...
Nidhi Baranwal23.6K visualizações
M ary psk modulation por Ahmed Diaa
M ary psk modulationM ary psk modulation
M ary psk modulation
Ahmed Diaa37.8K visualizações
DPCM por suryateja swamy
DPCMDPCM
DPCM
suryateja swamy28.2K visualizações
Signals & Systems PPT por Jay Baria
Signals & Systems PPTSignals & Systems PPT
Signals & Systems PPT
Jay Baria61K visualizações
quantization por aniruddh Tyagi
quantizationquantization
quantization
aniruddh Tyagi21.6K visualizações
NYQUIST CRITERION FOR ZERO ISI por FAIZAN SHAFI
NYQUIST CRITERION FOR ZERO ISINYQUIST CRITERION FOR ZERO ISI
NYQUIST CRITERION FOR ZERO ISI
FAIZAN SHAFI2.8K visualizações
1.introduction to signals por INDIAN NAVY
1.introduction to signals1.introduction to signals
1.introduction to signals
INDIAN NAVY2K visualizações
DSP_2018_FOEHU - Lec 07 - IIR Filter Design por Amr E. Mohamed
DSP_2018_FOEHU - Lec 07 - IIR Filter DesignDSP_2018_FOEHU - Lec 07 - IIR Filter Design
DSP_2018_FOEHU - Lec 07 - IIR Filter Design
Amr E. Mohamed8K visualizações
discrete time signals and systems por Zlatan Ahmadovic
 discrete time signals and systems  discrete time signals and systems
discrete time signals and systems
Zlatan Ahmadovic13.9K visualizações
Signals and classification por Suraj Mishra
Signals and classificationSignals and classification
Signals and classification
Suraj Mishra18.3K visualizações
Overview of sampling por Sagar Kumar
Overview of samplingOverview of sampling
Overview of sampling
Sagar Kumar8K visualizações
Ch1 por mihir jain
Ch1Ch1
Ch1
mihir jain4.8K visualizações
Digital communication systems unit 1 por Anil Nigam
Digital communication systems unit 1Digital communication systems unit 1
Digital communication systems unit 1
Anil Nigam11K visualizações
Signal and System, CT Signal DT Signal, Signal Processing(amplitude and time ... por Waqas Afzal
Signal and System, CT Signal DT Signal, Signal Processing(amplitude and time ...Signal and System, CT Signal DT Signal, Signal Processing(amplitude and time ...
Signal and System, CT Signal DT Signal, Signal Processing(amplitude and time ...
Waqas Afzal886 visualizações
Modulation por Nidhi Baranwal
ModulationModulation
Modulation
Nidhi Baranwal26K visualizações
Antenna por Naveen Sihag
AntennaAntenna
Antenna
Naveen Sihag46.6K visualizações
Modulation techniques por Sathish Kumar
Modulation techniquesModulation techniques
Modulation techniques
Sathish Kumar13.9K visualizações

Destaque

Sampling theory por
Sampling theorySampling theory
Sampling theoryDIPTENDU BASU
36.3K visualizações34 slides
Sampling por
SamplingSampling
Samplingsrkrishna341
17.6K visualizações28 slides
050 sampling theory por
050 sampling theory050 sampling theory
050 sampling theoryRaj Teotia
15.8K visualizações19 slides
Sampling theory por
Sampling theorySampling theory
Sampling theorySonali Srivastava
4.1K visualizações15 slides
Chapter6 sampling por
Chapter6 samplingChapter6 sampling
Chapter6 samplingKing Mongkut's University of Technology Thonburi
2.1K visualizações21 slides
Pulse modulation por
Pulse modulationPulse modulation
Pulse modulationstk_gpg
53.6K visualizações38 slides

Destaque(20)

Sampling theory por DIPTENDU BASU
Sampling theorySampling theory
Sampling theory
DIPTENDU BASU36.3K visualizações
Sampling por srkrishna341
SamplingSampling
Sampling
srkrishna34117.6K visualizações
050 sampling theory por Raj Teotia
050 sampling theory050 sampling theory
050 sampling theory
Raj Teotia15.8K visualizações
Sampling theory por Sonali Srivastava
Sampling theorySampling theory
Sampling theory
Sonali Srivastava4.1K visualizações
Pulse modulation por stk_gpg
Pulse modulationPulse modulation
Pulse modulation
stk_gpg53.6K visualizações
Theory of sampling por Jags Jagdish
Theory of samplingTheory of sampling
Theory of sampling
Jags Jagdish11.8K visualizações
Sampling methods PPT por Vijay Mehta
Sampling methods PPTSampling methods PPT
Sampling methods PPT
Vijay Mehta183.8K visualizações
sampling ppt por Swati Luthra
sampling pptsampling ppt
sampling ppt
Swati Luthra390.9K visualizações
Pulse code modulation por Abhijay Sisodia
Pulse code modulationPulse code modulation
Pulse code modulation
Abhijay Sisodia61.7K visualizações
RESEARCH METHOD - SAMPLING por Hafizah Hajimia
RESEARCH METHOD - SAMPLINGRESEARCH METHOD - SAMPLING
RESEARCH METHOD - SAMPLING
Hafizah Hajimia807.6K visualizações
PULSE CODE MODULATION (PCM) por vishnudharan11
PULSE CODE MODULATION (PCM)PULSE CODE MODULATION (PCM)
PULSE CODE MODULATION (PCM)
vishnudharan1163.4K visualizações
Sampling and Sample Types por Dr. Sunil Kumar
Sampling  and Sample TypesSampling  and Sample Types
Sampling and Sample Types
Dr. Sunil Kumar186.7K visualizações
Pulse code modulation por Naveen Sihag
Pulse code modulationPulse code modulation
Pulse code modulation
Naveen Sihag28.5K visualizações
Digital modulation por Muhd Iqwan Mustaffa
Digital modulationDigital modulation
Digital modulation
Muhd Iqwan Mustaffa31.7K visualizações
Digital Communication ppt por BZU lahore
Digital Communication pptDigital Communication ppt
Digital Communication ppt
BZU lahore41K visualizações
inverse z-transform ppt por mihir jain
inverse z-transform pptinverse z-transform ppt
inverse z-transform ppt
mihir jain10.2K visualizações

Similar a Sampling theorem

UPDATED Sampling Lecture (2).pptx por
UPDATED Sampling Lecture (2).pptxUPDATED Sampling Lecture (2).pptx
UPDATED Sampling Lecture (2).pptxHarisMasood20
1 visão83 slides
Signal & systems por
Signal & systemsSignal & systems
Signal & systemsAJAL A J
48.5K visualizações100 slides
Basic concepts por
Basic conceptsBasic concepts
Basic conceptsSyed Zaid Irshad
1.1K visualizações27 slides
Sns slide 1 2011 por
Sns slide 1 2011Sns slide 1 2011
Sns slide 1 2011cheekeong1231
2.8K visualizações100 slides
Data acquisition and conversion por
Data acquisition and conversionData acquisition and conversion
Data acquisition and conversionTejas Prajapati
131 visualizações18 slides
Classification of-signals-systems-ppt por
Classification of-signals-systems-pptClassification of-signals-systems-ppt
Classification of-signals-systems-pptMayankSharma1126
271 visualizações82 slides

Similar a Sampling theorem(20)

UPDATED Sampling Lecture (2).pptx por HarisMasood20
UPDATED Sampling Lecture (2).pptxUPDATED Sampling Lecture (2).pptx
UPDATED Sampling Lecture (2).pptx
HarisMasood201 visão
Signal & systems por AJAL A J
Signal & systemsSignal & systems
Signal & systems
AJAL A J48.5K visualizações
Basic concepts por Syed Zaid Irshad
Basic conceptsBasic concepts
Basic concepts
Syed Zaid Irshad1.1K visualizações
Sns slide 1 2011 por cheekeong1231
Sns slide 1 2011Sns slide 1 2011
Sns slide 1 2011
cheekeong12312.8K visualizações
Data acquisition and conversion por Tejas Prajapati
Data acquisition and conversionData acquisition and conversion
Data acquisition and conversion
Tejas Prajapati131 visualizações
Classification of-signals-systems-ppt por MayankSharma1126
Classification of-signals-systems-pptClassification of-signals-systems-ppt
Classification of-signals-systems-ppt
MayankSharma1126271 visualizações
Computational Intelligence for Time Series Prediction por Gianluca Bontempi
Computational Intelligence for Time Series PredictionComputational Intelligence for Time Series Prediction
Computational Intelligence for Time Series Prediction
Gianluca Bontempi708 visualizações
Ff tand matlab-wanjun huang por Sagar Ahir
Ff tand matlab-wanjun huangFf tand matlab-wanjun huang
Ff tand matlab-wanjun huang
Sagar Ahir1.3K visualizações
Ff tand matlab-wanjun huang por jhonce
Ff tand matlab-wanjun huangFf tand matlab-wanjun huang
Ff tand matlab-wanjun huang
jhonce497 visualizações
SP_BEE2143_C1.pptx por IffahSkmd
SP_BEE2143_C1.pptxSP_BEE2143_C1.pptx
SP_BEE2143_C1.pptx
IffahSkmd6 visualizações
Course-Notes__Advanced-DSP.pdf por ShreeDevi42
Course-Notes__Advanced-DSP.pdfCourse-Notes__Advanced-DSP.pdf
Course-Notes__Advanced-DSP.pdf
ShreeDevi4210 visualizações
Advanced_DSP_J_G_Proakis.pdf por HariPrasad314745
Advanced_DSP_J_G_Proakis.pdfAdvanced_DSP_J_G_Proakis.pdf
Advanced_DSP_J_G_Proakis.pdf
HariPrasad3147458 visualizações
Applications of Wavelet Transform por ijtsrd
Applications of Wavelet TransformApplications of Wavelet Transform
Applications of Wavelet Transform
ijtsrd219 visualizações
2. signal & systems beyonds por skysunilyadav
2. signal & systems  beyonds2. signal & systems  beyonds
2. signal & systems beyonds
skysunilyadav1.3K visualizações
Lecture 1 (ADSP).pptx por HarisMasood20
Lecture 1 (ADSP).pptxLecture 1 (ADSP).pptx
Lecture 1 (ADSP).pptx
HarisMasood2014 visualizações
Asp unit 1.pdf por ShreeDevi42
Asp unit 1.pdfAsp unit 1.pdf
Asp unit 1.pdf
ShreeDevi424 visualizações
Wavelet Multi-resolution Analysis of High Frequency FX Rates por aiQUANT
Wavelet Multi-resolution Analysis of High Frequency FX RatesWavelet Multi-resolution Analysis of High Frequency FX Rates
Wavelet Multi-resolution Analysis of High Frequency FX Rates
aiQUANT4.4K visualizações
Cyclostationary analysis of polytime coded signals for lpi radars por eSAT Journals
Cyclostationary analysis of polytime coded signals for lpi radarsCyclostationary analysis of polytime coded signals for lpi radars
Cyclostationary analysis of polytime coded signals for lpi radars
eSAT Journals158 visualizações
Chapter1 slide por asyrafjpk
Chapter1 slideChapter1 slide
Chapter1 slide
asyrafjpk2K visualizações

Último

dummy.pptx por
dummy.pptxdummy.pptx
dummy.pptxJamesLamp
7 visualizações2 slides
Basic Design Flow for Field Programmable Gate Arrays por
Basic Design Flow for Field Programmable Gate ArraysBasic Design Flow for Field Programmable Gate Arrays
Basic Design Flow for Field Programmable Gate ArraysUsha Mehta
10 visualizações21 slides
Ansari: Practical experiences with an LLM-based Islamic Assistant por
Ansari: Practical experiences with an LLM-based Islamic AssistantAnsari: Practical experiences with an LLM-based Islamic Assistant
Ansari: Practical experiences with an LLM-based Islamic AssistantM Waleed Kadous
12 visualizações29 slides
Renewal Projects in Seismic Construction por
Renewal Projects in Seismic ConstructionRenewal Projects in Seismic Construction
Renewal Projects in Seismic ConstructionEngineering & Seismic Construction
8 visualizações8 slides
Global airborne satcom market report por
Global airborne satcom market reportGlobal airborne satcom market report
Global airborne satcom market reportdefencereport78
8 visualizações13 slides
unit 1.pptx por
unit 1.pptxunit 1.pptx
unit 1.pptxrrbornarecm
5 visualizações53 slides

Último(20)

dummy.pptx por JamesLamp
dummy.pptxdummy.pptx
dummy.pptx
JamesLamp7 visualizações
Basic Design Flow for Field Programmable Gate Arrays por Usha Mehta
Basic Design Flow for Field Programmable Gate ArraysBasic Design Flow for Field Programmable Gate Arrays
Basic Design Flow for Field Programmable Gate Arrays
Usha Mehta10 visualizações
Ansari: Practical experiences with an LLM-based Islamic Assistant por M Waleed Kadous
Ansari: Practical experiences with an LLM-based Islamic AssistantAnsari: Practical experiences with an LLM-based Islamic Assistant
Ansari: Practical experiences with an LLM-based Islamic Assistant
M Waleed Kadous12 visualizações
Global airborne satcom market report por defencereport78
Global airborne satcom market reportGlobal airborne satcom market report
Global airborne satcom market report
defencereport788 visualizações
unit 1.pptx por rrbornarecm
unit 1.pptxunit 1.pptx
unit 1.pptx
rrbornarecm5 visualizações
Pitchbook Repowerlab.pdf por VictoriaGaleano
Pitchbook Repowerlab.pdfPitchbook Repowerlab.pdf
Pitchbook Repowerlab.pdf
VictoriaGaleano9 visualizações
2023Dec ASU Wang NETR Group Research Focus and Facility Overview.pptx por lwang78
2023Dec ASU Wang NETR Group Research Focus and Facility Overview.pptx2023Dec ASU Wang NETR Group Research Focus and Facility Overview.pptx
2023Dec ASU Wang NETR Group Research Focus and Facility Overview.pptx
lwang78314 visualizações
ASSIGNMENTS ON FUZZY LOGIC IN TRAFFIC FLOW.pdf por AlhamduKure
ASSIGNMENTS ON FUZZY LOGIC IN TRAFFIC FLOW.pdfASSIGNMENTS ON FUZZY LOGIC IN TRAFFIC FLOW.pdf
ASSIGNMENTS ON FUZZY LOGIC IN TRAFFIC FLOW.pdf
AlhamduKure10 visualizações
IRJET-Productivity Enhancement Using Method Study.pdf por SahilBavdhankar
IRJET-Productivity Enhancement Using Method Study.pdfIRJET-Productivity Enhancement Using Method Study.pdf
IRJET-Productivity Enhancement Using Method Study.pdf
SahilBavdhankar10 visualizações
Integrating Sustainable Development Goals (SDGs) in School Education por SheetalTank1
Integrating Sustainable Development Goals (SDGs) in School EducationIntegrating Sustainable Development Goals (SDGs) in School Education
Integrating Sustainable Development Goals (SDGs) in School Education
SheetalTank113 visualizações
Automated Remote sensing GPS satellite system for managing resources and moni... por Khalid Abdel Naser Abdel Rahim
Automated Remote sensing GPS satellite system for managing resources and moni...Automated Remote sensing GPS satellite system for managing resources and moni...
Automated Remote sensing GPS satellite system for managing resources and moni...
Khalid Abdel Naser Abdel Rahim5 visualizações
CCNA_questions_2021.pdf por VUPHUONGTHAO9
CCNA_questions_2021.pdfCCNA_questions_2021.pdf
CCNA_questions_2021.pdf
VUPHUONGTHAO97 visualizações
taylor-2005-classical-mechanics.pdf por ArturoArreola10
taylor-2005-classical-mechanics.pdftaylor-2005-classical-mechanics.pdf
taylor-2005-classical-mechanics.pdf
ArturoArreola1037 visualizações
Plant Design Report-Oil Refinery.pdf por Safeen Yaseen Ja'far
Plant Design Report-Oil Refinery.pdfPlant Design Report-Oil Refinery.pdf
Plant Design Report-Oil Refinery.pdf
Safeen Yaseen Ja'far9 visualizações
Module-1, Chapter-2 Data Types, Variables, and Arrays por Demian Antony D'Mello
Module-1, Chapter-2 Data Types, Variables, and ArraysModule-1, Chapter-2 Data Types, Variables, and Arrays
Module-1, Chapter-2 Data Types, Variables, and Arrays
Demian Antony D'Mello9 visualizações
Créativité dans le design mécanique à l’aide de l’optimisation topologique por LIEGE CREATIVE
Créativité dans le design mécanique à l’aide de l’optimisation topologiqueCréativité dans le design mécanique à l’aide de l’optimisation topologique
Créativité dans le design mécanique à l’aide de l’optimisation topologique
LIEGE CREATIVE9 visualizações
GPS Survery Presentation/ Slides por OmarFarukEmon1
GPS Survery Presentation/ SlidesGPS Survery Presentation/ Slides
GPS Survery Presentation/ Slides
OmarFarukEmon17 visualizações
REACTJS.pdf por ArthyR3
REACTJS.pdfREACTJS.pdf
REACTJS.pdf
ArthyR339 visualizações

Sampling theorem

  • 1. • Presented by., • S.Shanmathee Sampling Theorem
  • 3. ADC • Generally signals are analog in nature (eg:speech,weather signals). • To process the analog signal by digital means, it is essential to convert them to discrete-time signal , and then convert them to a sequence of numbers. • The process of converting an analog to digital signal is ‘Analog-to-Digital Conversion’. • The ADC involves three steps which are: 1)Sampling 2)Quantization 3)coding 2/6/2015
  • 4. • Analog signals: continuous in time and amplitude – Example: voltage, current, temperature,… • Digital signals: discrete both in time and amplitude – Example: attendance of this class, digitizes analog signals,… • Discrete-time signal: discrete in time, continuous in amplitude – Example: hourly change of temperature in Austin TYPES OF SIGNALS 2/6/2015
  • 5. • During sampling process, a continuous-time signal is converted into discrete -time signals by taking samples of continuous-time signal at discrete time intervals. )()( txnTsx  T=Sampling Interval x (t)=Analog input signal 2/6/2015
  • 6. •Sampling theorem gives the criteria for minimum number of samples that should be taken. •Sampling criteria:-”Sampling frequency must be twice of the highest frequency” fs=2W fs=sampling frequency w=higher frequency content 2w also known as Nyquist rate 2/6/2015
  • 7. •Nyquist rate is defined as the minimum sampling rate for the perfect reconstruction of the continuous time signals from samples. •Nyquist rate=2*highest frequency component =2*W •So sampling rate must be greater than or equal to nyquist rate 2/6/2015
  • 8. •There are two parts, representation of x(t) in its samples reconstruction of x(t) Representation of x(t) in its samples 1.Define x∂(t) 2.Take fourier transform of x∂(t)) (i.e) x∂(f) 3.Relation between x(f) and x∂(f) 4.Relation between x(t) and x(nTs) 2/6/2015
  • 9. Reconstruction of x(t) 1.Take inverse fourier transform of x∂(f) 2.Show that x(t) is obtained back with the help of interpolation function 2/6/2015
  • 10. •While providing sampling theorem we considered fs=2W •Consider the case that fs < 2W 2/6/2015
  • 11. Effects of Aliasing, 1.Distortion. 2.The data is lost and it cannot be recovered. To avoid Aliasing, 1.sampling rate must be fs>=2W. 2.strictly bandlimit the signal to ’W’. 2/6/2015
  • 13. In general form, any continuous signal can be written as S(t)=A1 cos(jw1t)+ A2 cos(jw2t)+ A3 cos(jw3t) F1= w1/2∏ = 50∏/2∏ = 25HZ F2= w2/2∏ = 300∏/2∏ = 150HZ F3= w3/2∏ = 100∏/2∏ = 50HZ Here, highest frequency component=150HZ Hence Nyquist rate=2*150HZ=300HZ )100cos(10)300sin(20)50cos(5)( tttts  2/6/2015
  • 14. •What is the minimum sampling rate(nyquist rate)? Highest frequency=100HZ So, Nyquist rate=2W=2*100=200HZ •If sampling frequency is 400HZ then what is the discrete time signal obtained? f=freq of continuous signal/sampling freq =100/400=1/4 Discrete time signal=5 cos(2∏fn)=5 cos (2∏*1/4 n) =5 cos(∏n/2) )200cos(5)( tts  2/6/2015
  • 16. Optimist: "The glass is half full." Pessimist: "The glass is half empty." Engineer: "That glass is twice as large as it needs to be." 2/6/2015