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Communication engineering and signal processing. Convolution, Fourier series and transform, amplitude modulation, angle modulation, random processes, noise in modulated systems, discrete signal processing, digital transmission (PCM, TDM and FDM), DTFT/DFT and FIR/IIR filter design.
Signal processing converts data into information. It is an essential component of many things we use/need/want in our daily lives. For example, computers, cell phones, internet, power grid, medical devices etc. Communications spreads that information. 5G, and beyond, communication standards need to be reliable enough for everything from medical applications, vehicle control and sensing, to smart-grid and home automation applications. This requires sophisticated, but computationally efficient signal processing techniques.In this course, we will show students the fundamentals of both signal processing and communications.Topics covered include:• Communication engineering and signal processing• Convolution and correlation• Fourier series and transform• Amplitude modulation• Angle modulation• Discrete signals and systems• Random processes• Generating digital signals (sampling and quantisation)• Fourier transform for discrete signals (DTFT/DFT)• Digital filter (FIR and IIR) design• Image processing
At the conclusion of this course you should be able to:• LO1: Describe and apply appropriate theories and mathematical techniques for use in analogue and digital signal processing (WA1, WA2)• LO2: Differentiate types of analogue and digital filters, and apply these filters in signal processing applications (WA2, WA3, WA4, WA11)• LO3: Process analogue and digital signals using contemporary mathematical techniques and tools for communication and other systems. (WA3, WA4, WA5)• LO4: Work collaboratively in a team environment (WA8)
This course will provide students with an opportunity to develop the Graduate Attributes specified below:
Critically competent in a core academic discipline of their award
Students know and can critically evaluate and, where applicable, apply this knowledge to topics/issues within their majoring subject.
Employable, innovative and enterprising
Students will develop key skills and attributes sought by employers that can be used in a range of applications.
ENEL220, EMTH210, ENEL321 and EMTH211
Students must attend one activity from each section.
Romain Arnal
Matthew Kokshoorn
B. P. Lathi, Zhi Ding; Modern digital and analog communication systems ; 5th Edition; Oxford University Press, 2019.
Artificial Intelligence ToolsThe use of Artificial Intelligence (AI) tools for each of the assessments in ENEL320 is summarised in the Table below. No AI use is allowed in the tests and exam because these are closed-book invigilated assessments. Students are always responsible for the accuracy of the submitted works, regardless of which tools are used.Assessment Item and Permitted use of AI AM Lab: Generative AI Tools Are Permitted for Certain Parts of This Assessment Test: Generative AI tools cannot be used for this assessment. Assignment: Generative AI Tools Are Permitted for Certain Parts of This Assessment Exam: Generative AI tools cannot be used for this assessment. Generative AI Tools Are Permitted for Certain Parts of This AssessmentIn these assessments (Lab Report, Assignment), you are permitted to use generative artificial intelligence (AI) for the purpose of proof reading and editing the document, and for gathering and summarising knowledge. No other use of generative AI is permitted. To assist with maintaining academic integrity, you must appropriately acknowledge any use of generative AI in your work. Please include a Statement of AI use (if no AI tool has been used, then this must also be stated) and a listing of all prompts provided to the AI tool, clearly indicating which AI tools were used and how they contributed to your assessment.
The examiners will award a failing grade to students who score less than 40% for the Tests and Exam combined. More formally, (TestPercent * 0.4 + ExamPercent * 0.5) / 0.9 must be greater than or equal to 40 for a pass mark to be awarded. This note is put in place to ensure that each student has adequately shown to the examiners they have gained some mastery of the topic.Assessment CompletionStudents must complete and submit the Assignment and Lab Report in order to be eligible to pass the course as defined in the General Conditions for Credit Regulations 3(a) here.Scaling of marksIn order to maintain consistency across courses and fairness for students, scaling of raw marks occurs. In the Faculty of Engineering, target course GPAs are calculated based on the performance of the cohort of students in their courses in the previous year. Scaling of the raw total course marks is normally performed so that when converted to grades (using UC Grade Scale) the outgoing GPA is in line with the target GPA for a course. Scaling up or down can occur.The Grading Scale for the University: https://www.canterbury.ac.nz/study/study-support-info/study-related-topics/grading-scale
Lateness PenaltiesFor the AM Lab and Assignment, a lateness penalty of 10% (in absolute terms) per day or part day late will be deducted from the original mark. For example, an assignment with a nominal mark of 83% submitted 0-24 hours late will receive a mark of 73%, and submitted 24-48 hours late will receive 63%.
Contact HoursLectures: 36 hoursTutorials: 12 hoursWorkshops: 0 hoursLaboratories: 6 hours Independent studyReview of lectures: 30 hoursExam preparation: 30 hoursAssignments: 12 hoursTutorial Preparation: 24 hoursTotal 150 hours
Domestic fee $1,190.00
International fee $6,488.00
* All fees are inclusive of NZ GST or any equivalent overseas tax, and do not include any programme level discount or additional course-related expenses.
For further information see Electrical and Computer Engineering .