Signals and Systems G (10093.2)
| Available teaching periods | Delivery mode | Location |
|---|---|---|
| View teaching periods | On-Campus |
Bruce, Canberra |
| EFTSL | Credit points | Faculty |
| 0.125 | 3 | Faculty Of Science And Technology |
| Discipline | Study level | HECS Bands |
| Academic Program Area - Technology | Graduate Level | Band 2 2021 (Commenced After 1 Jan 2021) Band 3 2021 (Commenced Before 1 Jan 2021) |
This unit may be cotaught with 8235 Signals and Systems.
Learning outcomes
On successful completion of this unit, students will be able to:1. Apply MATLAB for the solution of numerical problems in linear algebra, statistics, probability theory, sampling and quantisation. They will be able to interpret and utilise the important probability distribution functions, and apply appropriate statistical methodology; and
2. Utilise and apply sinusoids and exponentials as requisite and fundamental building blocks in the description of analog circuits and continuous systems, and in the representation of signals in the frequency domain. They will be able to interpret and evaluate the continuous and/or discrete sampling processes and apply strategies to avoid the problems of aliasing.
Graduate attributes
1. UC graduates are professional - communicate effectively1. UC graduates are professional - display initiative and drive, and use their organisation skills to plan and manage their workload
1. UC graduates are professional - employ up-to-date and relevant knowledge and skills
1. UC graduates are professional - take pride in their professional and personal integrity
1. UC graduates are professional - use creativity, critical thinking, analysis and research skills to solve theoretical and real-world problems
2. UC graduates are global citizens - adopt an informed and balanced approach across professional and international boundaries
2. UC graduates are global citizens - behave ethically and sustainably in their professional and personal lives
2. UC graduates are global citizens - make creative use of technology in their learning and professional lives
3. UC graduates are lifelong learners - adapt to complexity, ambiguity and change by being flexible and keen to engage with new ideas
3. UC graduates are lifelong learners - evaluate and adopt new technology
3. UC graduates are lifelong learners - reflect on their own practice, updating and adapting their knowledge and skills for continual professional and academic development
Prerequisites
None.Corequisites
None.Incompatible units
8235 Signals and Systems.Equivalent units
None.Assumed knowledge
None.| Year | Location | Teaching period | Teaching start date | Delivery mode | Unit convener |
|---|---|---|---|---|---|
| 2024 | Bruce, Canberra | Semester 2 | 29 July 2024 | On-Campus | Dr Maryam Ghahramani |
| 2025 | Bruce, Canberra | Semester 2 | 28 July 2025 | On-Campus | Dr Maryam Ghahramani |
Required texts
1. B. P. Lathi and R. A. Green, "Linear Systems and Signals", Oxford University Press, New York.
Submission of assessment items
Extensions & Late submissions
Assessment items must be submitted to the assignment area in the unit's UCLearn site, relating to that piece of assessment. It is the student's responsibility to upload the correct and corresponding draft or assessment item, to the right submission section.
Late submissions will only be accepted for a limited period. If more than one late submission is made within that period, only the first late submission will be accepted for marking and may be subject to penalties as detailed in the Assessment Procedures.
Extensions
Students can apply for an extension to the submission due date for an assessment item through extenuating, evidenced circumstances (specific details are found through the Assessment Policy and Procedures. Section 9.12). Extensions must be applied for before the due date. Documentary evidence (e.g. medical certificate) will be expected for an extension to be granted, however this will not guarantee that the application will be successful. The Unit Convener or relevant Discipline Convener will decide whether to grant an extension and the length of the extension.
An Assignment Extension form is available from the Student Forms page.
Late submission of assignments without an approved extension will result in a penalty of 5% reduced marks from the total available, per calendar day late. An assignment submitted over 7 days late will not be accepted.
Extensions: Extensions must be applied for before the due date.
Assessments and Lab report are meant to be individual work, although talking a problem over with another student or tutor is considered one reasonable way of learning. However, the actual submitted assignment must be the student's own work. Students are expected to familiarise themselves with the University's Student Academic Integrity Policy. Experience has shown that students who do not do their own work are unlikely to pass the exam (and therefore the unit).
Assessments and Lab report will be submitted electronically through the Unit Website interface on UC Learn (Canvas). Submissions must be done in PDF format to avoid problems in reading documents made on different platforms / using different software. However, codes and simulations are expected to be compiled and uploaded as a plain text file.
Assignment submissions will be assessed for addressing the specific requirements of each assignment, as stated in the assignment descriptions. Assignment submissions will receive a numerical mark, which together in their entirety with the other assessment items (test, exam) define a student's final grade as outlined below.
Special assessment requirements
Final Mark:
An aggregate mark of 50% is required to pass the unit in addition to achieving at least 50% in the Second Assignment.
The unit convener reserves the right to question students orally on any of their submitted work and modify the mark/grade accordingly if needed.
| Grade |
Assessments |
| Pass |
Minimum 50% of combined weighted marks of all assessment items |
| Credit |
Minimum 65% of combined weighted marks of all assessment items |
| Distinction |
Minimum 75% of combined weighted marks of all assessment items |
| High Distinction |
Minimum 85% of combined weighted marks of all assessment items |
Academic integrity
Students have a responsibility to uphold University standards on ethical scholarship. Good scholarship involves building on the work of others and use of others' work must be acknowledged with proper attribution made. Cheating, plagiarism, and falsification of data are dishonest practices that contravene academic values. Refer to the University's Student Charter for more information.
To enhance understanding of academic integrity, all students are expected to complete the Academic Integrity Module (AIM) at least once during their course of study. You can access this module within UCLearn (Canvas) through the 'Academic Integrity and Avoiding Plagiarism' link in the Study Help site.
Use of Text-Matching Software
The University of Canberra uses text-matching software to help students and staff reduce plagiarism and improve understanding of academic integrity. The software matches submitted text in student assignments against material from various sources: the internet, published books and journals, and previously submitted student texts.
Learner engagement
Expected Average Student Workload:
Lectures 24h
Lecture Reviews 12h
Tutorials and Laboratories + Preparation (laboratories) 40h
First Assignment 24h
Research Paper 20h
Second Assignment 30h
Total: 150 Hours
Participation requirements
Students are expected to attend/watch all lectures, and are needed to attend all laboratory classes. Engagement with the activity in tutorials and laboratory classes will assist your preparation for the assessment tasks. Participation in both class and online activities will enhance understanding of the unit content and therefore the quality of the assessment responses. Participation in laboratory/practical classes is a compulsory condition of this unit, and attendance will be recorded. You must participate in at least 8 of tutorial/laboratory classes to pass this unit. In the event that you cannot attend your assigned laboratory class due to illness or unavoidable commitments, contact the Unit Convener as soon as possible.
Required IT skills
Basic programming skills for the use of MATLAB (lecturer will assist with MATLAB) and Python.
Work placement, internships or practicums
Not applicable to this unit
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