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Thanks to:
Y. C. Kuang and Melanie Ooi 2006
J. A. Bennett 2007
J Zhang 2009-2010
E. Viterbo 2011-2014
ECE 2011
Signal Processing
2
ECE 2011 Signal Processing
• Unit Coordinator and Lecturer:
Dr Yi Hong – Office: Room 224/Bld.72 email: [email protected]
• Lecture notes available on Moodle
• Head of Tutors and Lab Demonstrators
• Mohammad Morshed email: [email protected]
• Tutors and Lab Demonstrators
Dimuthu Jayasingha <[email protected]>,
Lin Yun Huang <[email protected]>,
Md Bhuiyan <[email protected]>,
Emran Amin <[email protected]>,
Aminul Islam <[email protected]>,
Anee Azim <[email protected]>,
Muhsiul Hassan <[email protected]>,
Omar Arafat <[email protected]>,
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Prescribed Text
Signal Processing First
McClellan, J., Schafer, R.
and Yoder, M.
Pearson Prentice Hall
2003
4
References
• Recommended Reading
– Linear System and Signal, Lathi
– Signal and Systems, Oppenheim
• Useful References
– Digital Signal Processing, Mitra
5
Course Attributes
• 6 credit points
• 12 x 3 lectures
• 11 x 1 hour tutorials
• 11 x 2 hours of laboratory works (Compulsory)
• Assessment: 3-hour examination: 70%
• Lab tasks verification: 10%
• Quiz: 10%
• Lab test: 10%
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Course Attributes
Assessment
Task
Val
ue
45% Pass Total pass Due Date
1. Lab tasks
verification
10
%
30%
>13.5/30
>50%
During and at the
end of each lab.
Week 2-12
2.Quiz 10
%
During and at the
end of each tutorial.
Week 2-12
3.Lab test 10
%
Week 12
4. Examination (3
hours)
70% >31.5/70
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Course Attributes
All laboratory classes are compulsory even for repeating students. To
achieve a pass in the unit students must achieve a mark of 45% in each
of the assessment components and an overall mark of 50%.
Assessment Task 1: Lab tasks verification (Week 2- Week 11)
Details of task:
During each lab, upon completion of each task, students are required to
demonstrate their experiment results to the demonstrators before proceed
to the next lab task. At the end of each lab, students are required to ask
the lab demonstrators to verify their entire experiment results and sign off
Verification Form. Students must keep an individual lab logbook recording
the details of lab experiment.
Criteria for Assessment task 1:
As stated in the instruction of each lab/tutorial
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Course Attributes
Assessment Task 2: Quiz (Week 1 – Week 11)
Details of task: A weekly quiz will be based on MCQ type questions and
numerical problems.
Criteria for Assessment task 2:
Number of correct answers
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Course Attributes
Assessment Task 3: Lab test (Week 12)
Details of task:
Computer based written test that covers all the labs over the semester.
Students are required to complete independently and individually a set of
tasks selected from the labs they performed over the semester. Students
are allowed to use their lab logbook in the test.
Criteria for Assessment task 3:
Use of correct concepts
MATLAB programming
Correct and accurate computation results
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Week1
• No Lab this week.
• Tutorials are on this week (Revision on
complex number, Phasors, etc)
• Quiz 1 is on.
• MULO recoding lecture
• http://www.mulo.monash.edu.au/ece2011
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Online Moodle Quizzes
• All questions carry equal marks.
• Three attempts will be allowed for each quiz every week.
• The best result out of three will be marked.
• Quizzes are open for attempt from Tuesday afternoon till
Monday 9am
• Correct answers will appear after a quiz is closed Monday 9am
• Mainly two types of questions.
– Multiple choice questions: Choose the correct answer from a set of answers
– Calculated answer questions: Calculate a numerical answer (Do not enter the
units with a numerical answer; i.e. if answer is 1000 Hz enter only 1000)
• Answers to questions need to be submitted
– Open attempts that are not submitted are automatically submitted when
the quiz period lapses.
• The best 7 quizzes scores out of 10 will form the final 10% mark
– First week is just to warm up, last week is for lab test
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To Ensure Good Results
• Attend all lectures then try quizzes
• Revise the lecture notes and read the
references within 2 days
• Attend all tutorials and participate
• Practice
• Practice
• Practice
Very
important !
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• Read up before attending lecture
• Attempt the tutorial questions and other
questions from books
• Miss a lecture ?
– At least 2 hours studying the textbook and
resolve any queries with lecturer ASAP
• Seek help early if there is any problem
– Last minute rush is a perfect recipe for
disaster
To Ensure Good Results
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Tutorials
• Group studies is recommended
– Form groups of 3 ~ 6
– Helping your friends will help to deepen your own
understanding of the subject
• Discuss your solution with your friends before
coming to tutorial and laboratory session
• Make sure you can do the tutorial questions using
pen and paper
• You are responsible for your own studies
in the university !
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• Consultation
– Tutorial session
• Activities during tutorial session:
1. Attempt tutorial questions
2. Feedback on coursework / test
3. Discussion of new concepts in the lecture
4. Discussion of upcoming laboratory
exercises
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Problem with Tutorial Problems
• First stop: Textbook / Supporting CD
– Study the examples
– Read the textbook again
• Second stop: Friends
– Discussion helps (a lot)
• Third stop: Yourself
– Reflect deeply on the topic
• Desperate: Helpdesk
– Don’t give up easily
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Laboratory/Tutorials
• Two-hour sessions per week Labs (check Allocate)
• One our session tutorial per week (check Allocate)
• Group of 2 or individual
• Within 12 weeks
– 10 laboratory exercises
• Most laboratory exercises come with some preliminary
works
– Some come with extra exercises and quizzes
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Preliminary Works
• Must be completed prior to the start of
the main exercises
• Submit at beginning of every laboratory
session
• Let lab demonstrator sign off lab tasks
on lab verification pages upon
completion of the tasks
• Sign attendance at the same time
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Laboratory Exercises
• Exercises after preliminary work are aimed
at assisting the understanding of difficult
concepts
– Normally time consuming
– Ideally should be done before attending the
laboratory sessions
– They are mostly interactive using MATLAB
• You might be quizzed to test your
understanding
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Lab Schedule
• Check your time in Allocate+, there might
be changes before Week 2.
• I cannot change your allocation, if you
have a timetable collision you need to
contact the Faculty Office building 72.
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Unit Objectives
• Understanding of continuous and discrete time signals
– Mathematical modeling & analysis of signals for signal and information processing
– Relevant to all fields of engineering, science and beyond
• Frequency domain representation and analysis
– Most powerful analytical tool to deal with signals and linear systems
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Objectives
• Properties of linear time invariant
systems
– Simple model of real systems
– Very useful first approximation
• Fourier Transforms
– Time frequency transformation
– Most widely used in applied science and
engineering
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Objectives
• To develop the ability to:
– Relate time domain and frequency domain analyses and interpret the results properly
– Aware of the presence of sampling errors, aliasing, windowing and other artifacts introduced into the data due to signal processing techniques
– Recognize the implications of signal processing technique and existence of man-made artifacts in the signal
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Relevance & Applications
• Measurement instrumentation, control feedback
– Oscilloscope, position measurement GPS, etc
• Communication
– Mobile phone, radar, television, etc.
• Medical imaging
– MRI, CT, Ultrasound, etc.
• Almost all scientific/engineering works
– Hardly any modern example does not need signal
processing technique
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Simple Linear Filtering
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Major Topics
1. Continuous & discrete signals
• Sinusoid and phasors
• General signals
• Sampling theory
• Spectrum
2. Transforms
• Fourier transform
• Z – transform
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Major Topics
3. Filters and linear systems
• Convolution
• FIR filters/systems
• IIR filters/systems
4. Applications
• Denoising
• Spectrum analysis
• Signal conditioning
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Prerequisites
• Integration
– Trigonometry and exponential functions
• Complex number
– Euler’s relation
• MATLAB programming
– Extensively used in the laboratory exercises
– Solving more realistic examples
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Integration
Complex number
MATLAB programming
No excuses please
