Transcript Intro - The University of Jordan

EE 701
Digital Signal Processing and
Filtering
Instructor: Dr. Ghazi Al Sukkar
Dept. of Electrical Engineering
The University of Jordan
Email: [email protected]
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Course Details
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Objective
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Establish a background in Digital Signal Processing Theory
Design and implementation of DSP algorithms
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Discrete-Time Signal Processing,
Prentice Hall, 3rd Edition
Alan V. Oppenheim, Ronald W. Schafer
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Assignments
Project (term paper)
Midterm Exam
Final Exam
Text Book
Grading
-
10%
20%
30%
40%
Note: send me an email (in the subject EE701) to assign
you the term paper.
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Useful References
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Digital Signal processing, by John Proakis and Dimitris G. Monalakis.
Digital Signal Processing, A computer based approach, third edition, by
Sanjit K. Mitra.
Digital Signal Processing, Sanjit H. Mitra. Mc Graw Hill, 3rd Ed. 2006
Digital Signal Processing, R.A. Roberts and C.T. Mullis. AddisonWesley, 1996.
Real-Time Digital Signal Processing, Sen M. Kuo and Bob H. Lee,
Wiley, 2001.
Optimum Signal Processing, S. Orfanidis, MacMillan, 1988.
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Course Website
http://www2.ju.edu.jo/sites/Academic/ghazi.alsukkar/
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Course Outline
 Topic 1
Discrete-Time Signals and
Systems + LTI
 Topic 2
The Z-Transform
 Topic 3
Sampling of Continuous Time
Signals
 Topic 4
Transform Analysis of Linear
Time-Invariant Systems
 Topic 5
Structures of Discrete-Time
Systems
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Outline
 Topic 6
FIR and IRR Discrete Filter
Design Techniques
 Topic 7
The Discrete Fourier
Transform (DFT)
 Topic 8
Computation of the Discrete
Fourier Transform
 Topic 9
Applications of Digital Signal
Processing
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Where is DSP
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DSP is Everywhere
 Sound applications
 Compression, enhancement, special effects,
synthesis, recognition, echo cancellation,…
 Cell Phones, MP3 Players, Movies, Dictation, Text-tospeech,…
 Communication
 Modulation, coding, detection, equalization, echo
cancellation,…
 Cell Phones, dial-up modem, DSL modem, Satellite
Receiver,…
 Automotive
 ABS, GPS, Active Noise Cancellation, Cruise Control,
Parking,…
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DSP Application
 Medical
 Magnetic Resonance, Tomography,
Electrocardiogram,…
 Military
 Radar, Sonar, Space photographs, remote
sensing,…
 Image and Video Applications
 DVD, JPEG, Movie special effects, video
conferencing,…
 Mechanical
 Motor control, process control, oil and mineral
prospecting,…
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Signal Processing
 Humans are the most advanced signal processors
 speech and pattern recognition, speech synthesis,…
 We encounter many types of signals in various
applications
 Electrical signals: voltage, current, magnetic and
electric fields,…
 Mechanical signals: velocity, force, displacement,…
 Acoustic signals: sound, vibration,…
 Other signals: pressure, temperature,…
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Signal processing
 Most real-world signals are analog
 They are continuous in time and amplitude
 Convert to voltage or currents using sensors and
transducers
 Analog circuits process these signals using
 Resistors, Capacitors, Inductors, Amplifiers,…
 Analog signal processing examples
 Audio processing in FM radios
 Video processing in traditional TV sets
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Limitations of Analog Signal
Processing
 Accuracy limitations due to
 Component tolerances
 Undesired nonlinearities
 Limited repeatability due to
 Tolerances
 Changes in environmental conditions
 Temperature
 Vibration
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Cont..
 Sensitivity to electrical noise
 Inflexibility to changes
 Limited dynamic range for voltage
and currents
 Difficulty of implementing certain
operations
 Nonlinear operations
 Time-varying operations
 Difficulty of storing information
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Digital Signal Processing
 Represent signals by a sequence of numbers
 Sampling or analog-to-digital conversions
 Perform processing on these numbers with a digital
processor
 Digital signal processing
 Reconstruct analog signal from processed numbers
 Reconstruction or digital-to-analog conversion
analog
signal
A/D
digital
signal
DSP
digital
signal
D/A
analog
signal
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Input vs. Output
 Analog input – analog output
 Digital recording of music
 Analog input – digital output
 Touch tone phone dialing
 Digital input – analog output
 Text to speech
 Digital input – digital output
 Compression of a file on computer
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Advantages and disadvantages
of Digital Signal Processing
 Advantages
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Accuracy can be controlled by choosing word length
Repeatable
Sensitivity to electrical noise is minimal
Dynamic range can be controlled using floating point
numbers
Flexibility can be achieved with software implementations
Non-linear and time-varying operations are easier to
implement
Digital storage is cheap
Digital information can be encrypted for security
Price/performance and reduced time-to-market
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Cont..
 Disadvantages
 Sampling causes loss of information
 A/D and D/A requires mixed-signal
hardware
 Limited speed of processors!!!
 Quantization and round-off errors
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