Students

ELEC240 – Signals and Systems

2016 – S2 Day

General Information

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Unit convenor and teaching staff Unit convenor and teaching staff Lecturer (weeks 8-13)
Sam Reisenfeld
Wednesday 3-5pm
Lecturer (weeks 1-7) and Convenor
Stephen Hanly
Wednesday 4-5pm, Thursday 4-5pm
Head tutor
Audri Biswas
tutor
Ahsan Ali
Credit points Credit points
3
Prerequisites Prerequisites
12cp including (MATH136(P) or MATH133)
Corequisites Corequisites
Co-badged status Co-badged status
Unit description Unit description
The aim of this unit is to give students a comprehensive introduction to the theory of signal processing and analysis that is used in many areas of electronic and telecommunications engineering including: circuit analysis; amplifiers and electronic systems; analogue and digital communications; audio and image processing; and control systems. The unit covers time and frequency analysis for both continuous-time and discrete-time signals. Topics covered in the unit include: linear time-invariant systems; convolution; Fourier series; Fourier transforms; Discrete Fourier transforms; and Z transforms.

Important Academic Dates

Information about important academic dates including deadlines for withdrawing from units are available at https://www.mq.edu.au/study/calendar-of-dates

Learning Outcomes

On successful completion of this unit, you will be able to:

  • Demonstrated use of Matlab to solve problems in Signals and Systems
  • Be able to solve signal processing problems involving Complex Numbers
  • Demonstrated understanding of how signals can be scaled in space, time, flipped in time (time-reversal), delayed (right and left shifted), and other signal properties (mean, energy, power, periodicity)
  • Demonstrated understanding of the concept of a linear time-invariant system and its use in modeling the input-output relationship for signals in many applications.
  • Demonstrated understanding of the concept of signal domains: how the same signal can be represented in different domains (in time or in frequency) and how to transform from one representation to another.
  • Demonstrated understanding of the role of sampling and filtering in converting between continuous-time to discrete-time signals, including the Nyquist criterion, and concept of aliasing.
  • Demonstrated understanding of the relationship between the tools used in discrete-time and continuous-time signal processing, and to be able to find the appropriate signal domain and transform method to find system outputs from system inputs in a variety of applications (eg circuits, filters, communication channels)
  • Demonstrated ability in the following areas of professional engineering practice: –self motivation and self learning –Production of quality work to meet a given deadline

General Assessment Information

An overall mark of 50 or more is required to pass the unit (P/CR/D/HD)

Assessment Tasks

Name Weighting Due
practicals held each week 20% weekly
Assignment 1 4% 19/08/2016
test 10% 22/08/2016
Assignment 2 4% 12/09/2016
Assignment 3 4% 4/10/2016
Assignment 4 4% 17/10/2016
Assignment 5 4% 11/11/2016
End of Semester Exam 50% scheduled in final exam period

practicals held each week

Due: weekly
Weighting: 20%

Two test questions during each practical session scheduled in weeks 1-13


On successful completion you will be able to:
  • Demonstrated use of Matlab to solve problems in Signals and Systems

Assignment 1

Due: 19/08/2016
Weighting: 4%

Problems on differential equations and complex numbers


On successful completion you will be able to:
  • Be able to solve signal processing problems involving Complex Numbers
  • Demonstrated ability in the following areas of professional engineering practice: –self motivation and self learning –Production of quality work to meet a given deadline

test

Due: 22/08/2016
Weighting: 10%

In-class test on complex numbers and signal properties


On successful completion you will be able to:
  • Be able to solve signal processing problems involving Complex Numbers

Assignment 2

Due: 12/09/2016
Weighting: 4%

Problems on linear time-invariant systems, convolution and impulse response


On successful completion you will be able to:
  • Demonstrated understanding of how signals can be scaled in space, time, flipped in time (time-reversal), delayed (right and left shifted), and other signal properties (mean, energy, power, periodicity)
  • Demonstrated ability in the following areas of professional engineering practice: –self motivation and self learning –Production of quality work to meet a given deadline

Assignment 3

Due: 4/10/2016
Weighting: 4%

Problems on Fourier Series, Fourier Transform, and Transfer function of a linear time-invariant system


On successful completion you will be able to:
  • Demonstrated understanding of the concept of a linear time-invariant system and its use in modeling the input-output relationship for signals in many applications.
  • Demonstrated understanding of the concept of signal domains: how the same signal can be represented in different domains (in time or in frequency) and how to transform from one representation to another.
  • Demonstrated ability in the following areas of professional engineering practice: –self motivation and self learning –Production of quality work to meet a given deadline

Assignment 4

Due: 17/10/2016
Weighting: 4%

Problems on sampling, aliasing and Nyquist criterion in time and frequency domain


On successful completion you will be able to:
  • Demonstrated understanding of the role of sampling and filtering in converting between continuous-time to discrete-time signals, including the Nyquist criterion, and concept of aliasing.
  • Demonstrated ability in the following areas of professional engineering practice: –self motivation and self learning –Production of quality work to meet a given deadline

Assignment 5

Due: 11/11/2016
Weighting: 4%

Problems on Z Transform, Discrete-time Fourier Transform, solving difference equations


On successful completion you will be able to:
  • Demonstrated understanding of the concept of signal domains: how the same signal can be represented in different domains (in time or in frequency) and how to transform from one representation to another.
  • Demonstrated understanding of the relationship between the tools used in discrete-time and continuous-time signal processing, and to be able to find the appropriate signal domain and transform method to find system outputs from system inputs in a variety of applications (eg circuits, filters, communication channels)

End of Semester Exam

Due: scheduled in final exam period
Weighting: 50%

Final exam


On successful completion you will be able to:
  • Demonstrated understanding of how signals can be scaled in space, time, flipped in time (time-reversal), delayed (right and left shifted), and other signal properties (mean, energy, power, periodicity)
  • Demonstrated understanding of the concept of a linear time-invariant system and its use in modeling the input-output relationship for signals in many applications.
  • Demonstrated understanding of the concept of signal domains: how the same signal can be represented in different domains (in time or in frequency) and how to transform from one representation to another.
  • Demonstrated understanding of the role of sampling and filtering in converting between continuous-time to discrete-time signals, including the Nyquist criterion, and concept of aliasing.
  • Demonstrated understanding of the relationship between the tools used in discrete-time and continuous-time signal processing, and to be able to find the appropriate signal domain and transform method to find system outputs from system inputs in a variety of applications (eg circuits, filters, communication channels)

Delivery and Resources

Required and Recommended texts and/or materials

The textbook used is “Signals, Systems and Transforms” 4th ed, by Phillips, Parr and Riskin. Pearson publishers. 2008.

 Matlab & Simulink Student Version Software by the MathWorks is highly recommended.

There are many other books in signal processing in the library. Books which cover similar material to ELEC240 include:

“Signals and systems”, M. J. Roberts, McGraw-Hill.2004.

“An Introduction to Signals and Systems”, J. A. Stuller, Thomson publishers, 2008.

“Linear Systems and Signals”, 2nd ed, B. P. Lathi, Oxford University Press, 2005.

“Digital Signal Processing. Principles, Algorithms and Applications”, 4th ed, J. G. Proakis and D. G. Manolakis, Pearson publishers, 2007.

“Signals and systems”, S. Haykin and B. Van Veen, John Wiley &b Sons. 1999.

More advanced books include:

“Discrete-time signal processing”, A. V. Oppenheim and R. W. Schafer with J. R. Buck, Prentice-Hall, 1999.

“Signals & Systems”, A. V. Oppenheim and A. S. Willsky with S. H. Nawab, Prentice-Hall, 1997.

 Unit Web Page

Unit lecture notes, resources, assignments and other information about the unit can be accessed through iLearn.

 

Technology used

Library and internet search engines, word processing software. The primary software tool used in practicals is Matlab.

Practical Sessions

Attendance at laboratory sessions is compulsory. Any student who is absent from more than two sessions may not be permitted to sit the examinations.

Experimental work and reports are to be written during the laboratory sessions with reports to be viewed by the tutors. Test questions must be undertaken during the practical sessions and marked by the tutors during those sessions. It is prohibited to use the computers in the laboratory for any purpose other than as directed.

Practical Session Safety

No student will be permitted to enter the laboratory without proper footwear. THONGS OR SANDALS ARE NOT ACCEPTABLE. NO FOOD OR DRINK may be taken into the laboratory.

 

Policies and Procedures

Macquarie University policies and procedures are accessible from Policy Central. Students should be aware of the following policies in particular with regard to Learning and Teaching:

Academic Honesty Policy http://mq.edu.au/policy/docs/academic_honesty/policy.html

New Assessment Policy in effect from Session 2 2016 http://mq.edu.au/policy/docs/assessment/policy_2016.html. For more information visit http://students.mq.edu.au/events/2016/07/19/new_assessment_policy_in_place_from_session_2/

Assessment Policy prior to Session 2 2016 http://mq.edu.au/policy/docs/assessment/policy.html

Grading Policy prior to Session 2 2016 http://mq.edu.au/policy/docs/grading/policy.html

Grade Appeal Policy http://mq.edu.au/policy/docs/gradeappeal/policy.html

Complaint Management Procedure for Students and Members of the Public http://www.mq.edu.au/policy/docs/complaint_management/procedure.html​

Disruption to Studies Policy http://www.mq.edu.au/policy/docs/disruption_studies/policy.html The Disruption to Studies Policy is effective from March 3 2014 and replaces the Special Consideration Policy.

In addition, a number of other policies can be found in the Learning and Teaching Category of Policy Central.

Student Code of Conduct

Macquarie University students have a responsibility to be familiar with the Student Code of Conduct: https://students.mq.edu.au/support/student_conduct/

Results

Results shown in iLearn, or released directly by your Unit Convenor, are not confirmed as they are subject to final approval by the University. Once approved, final results will be sent to your student email address and will be made available in eStudent. For more information visit ask.mq.edu.au.

Student Support

Macquarie University provides a range of support services for students. For details, visit http://students.mq.edu.au/support/

Learning Skills

Learning Skills (mq.edu.au/learningskills) provides academic writing resources and study strategies to improve your marks and take control of your study.

Student Services and Support

Students with a disability are encouraged to contact the Disability Service who can provide appropriate help with any issues that arise during their studies.

Student Enquiries

For all student enquiries, visit Student Connect at ask.mq.edu.au

IT Help

For help with University computer systems and technology, visit http://www.mq.edu.au/about_us/offices_and_units/information_technology/help/

When using the University's IT, you must adhere to the Acceptable Use of IT Resources Policy. The policy applies to all who connect to the MQ network including students.

Graduate Capabilities

Capable of Professional and Personal Judgement and Initiative

We want our graduates to have emotional intelligence and sound interpersonal skills and to demonstrate discernment and common sense in their professional and personal judgement. They will exercise initiative as needed. They will be capable of risk assessment, and be able to handle ambiguity and complexity, enabling them to be adaptable in diverse and changing environments.

This graduate capability is supported by:

Learning outcomes

  • Demonstrated use of Matlab to solve problems in Signals and Systems
  • Demonstrated ability in the following areas of professional engineering practice: –self motivation and self learning –Production of quality work to meet a given deadline

Assessment tasks

  • Assignment 3
  • Assignment 4
  • Assignment 5

Commitment to Continuous Learning

Our graduates will have enquiring minds and a literate curiosity which will lead them to pursue knowledge for its own sake. They will continue to pursue learning in their careers and as they participate in the world. They will be capable of reflecting on their experiences and relationships with others and the environment, learning from them, and growing - personally, professionally and socially.

This graduate capability is supported by:

Learning outcome

  • Demonstrated ability in the following areas of professional engineering practice: –self motivation and self learning –Production of quality work to meet a given deadline

Assessment tasks

  • practicals held each week
  • Assignment 1
  • test
  • Assignment 2
  • Assignment 3
  • Assignment 4
  • Assignment 5

Discipline Specific Knowledge and Skills

Our graduates will take with them the intellectual development, depth and breadth of knowledge, scholarly understanding, and specific subject content in their chosen fields to make them competent and confident in their subject or profession. They will be able to demonstrate, where relevant, professional technical competence and meet professional standards. They will be able to articulate the structure of knowledge of their discipline, be able to adapt discipline-specific knowledge to novel situations, and be able to contribute from their discipline to inter-disciplinary solutions to problems.

This graduate capability is supported by:

Learning outcomes

  • Demonstrated use of Matlab to solve problems in Signals and Systems
  • Be able to solve signal processing problems involving Complex Numbers
  • Demonstrated understanding of how signals can be scaled in space, time, flipped in time (time-reversal), delayed (right and left shifted), and other signal properties (mean, energy, power, periodicity)
  • Demonstrated understanding of the concept of a linear time-invariant system and its use in modeling the input-output relationship for signals in many applications.
  • Demonstrated understanding of the concept of signal domains: how the same signal can be represented in different domains (in time or in frequency) and how to transform from one representation to another.
  • Demonstrated understanding of the role of sampling and filtering in converting between continuous-time to discrete-time signals, including the Nyquist criterion, and concept of aliasing.
  • Demonstrated understanding of the relationship between the tools used in discrete-time and continuous-time signal processing, and to be able to find the appropriate signal domain and transform method to find system outputs from system inputs in a variety of applications (eg circuits, filters, communication channels)

Assessment tasks

  • practicals held each week
  • Assignment 1
  • test
  • Assignment 2
  • Assignment 3
  • Assignment 4
  • Assignment 5
  • End of Semester Exam

Critical, Analytical and Integrative Thinking

We want our graduates to be capable of reasoning, questioning and analysing, and to integrate and synthesise learning and knowledge from a range of sources and environments; to be able to critique constraints, assumptions and limitations; to be able to think independently and systemically in relation to scholarly activity, in the workplace, and in the world. We want them to have a level of scientific and information technology literacy.

This graduate capability is supported by:

Learning outcomes

  • Demonstrated use of Matlab to solve problems in Signals and Systems
  • Demonstrated understanding of the concept of a linear time-invariant system and its use in modeling the input-output relationship for signals in many applications.
  • Demonstrated understanding of the concept of signal domains: how the same signal can be represented in different domains (in time or in frequency) and how to transform from one representation to another.
  • Demonstrated understanding of the role of sampling and filtering in converting between continuous-time to discrete-time signals, including the Nyquist criterion, and concept of aliasing.
  • Demonstrated understanding of the relationship between the tools used in discrete-time and continuous-time signal processing, and to be able to find the appropriate signal domain and transform method to find system outputs from system inputs in a variety of applications (eg circuits, filters, communication channels)

Assessment tasks

  • practicals held each week
  • Assignment 2
  • Assignment 3
  • Assignment 4
  • Assignment 5
  • End of Semester Exam

Problem Solving and Research Capability

Our graduates should be capable of researching; of analysing, and interpreting and assessing data and information in various forms; of drawing connections across fields of knowledge; and they should be able to relate their knowledge to complex situations at work or in the world, in order to diagnose and solve problems. We want them to have the confidence to take the initiative in doing so, within an awareness of their own limitations.

This graduate capability is supported by:

Learning outcomes

  • Demonstrated use of Matlab to solve problems in Signals and Systems
  • Demonstrated understanding of the concept of signal domains: how the same signal can be represented in different domains (in time or in frequency) and how to transform from one representation to another.
  • Demonstrated understanding of the role of sampling and filtering in converting between continuous-time to discrete-time signals, including the Nyquist criterion, and concept of aliasing.
  • Demonstrated understanding of the relationship between the tools used in discrete-time and continuous-time signal processing, and to be able to find the appropriate signal domain and transform method to find system outputs from system inputs in a variety of applications (eg circuits, filters, communication channels)

Assessment tasks

  • practicals held each week
  • Assignment 3
  • Assignment 4
  • Assignment 5
  • End of Semester Exam

Effective Communication

We want to develop in our students the ability to communicate and convey their views in forms effective with different audiences. We want our graduates to take with them the capability to read, listen, question, gather and evaluate information resources in a variety of formats, assess, write clearly, speak effectively, and to use visual communication and communication technologies as appropriate.

This graduate capability is supported by:

Learning outcome

  • Demonstrated ability in the following areas of professional engineering practice: –self motivation and self learning –Production of quality work to meet a given deadline

Assessment tasks

  • practicals held each week
  • Assignment 1
  • test
  • Assignment 2
  • Assignment 3
  • Assignment 4
  • Assignment 5
  • End of Semester Exam

Changes from Previous Offering

There is less material on solving linear constant coefficient differential equations; the focus is on obtaining steady-state solutions. Laplace transforms are not covered.