PHYSICS 340 : Electronics and Signal Processing

Science

2020 Semester One (1203) (15 POINTS)

Course Prescription

Electronics and digital signal processing with a strong emphasis on practical circuit design and data acquisition techniques. Topics will be selected from: linear circuit theory, analytical and numeric network analysis, feedback and oscillation, operational amplifier circuits, Fourier theory, sampling theory, digital filter design, and the fast Fourier transform.

Course Overview

This course covers aspects of both practical electronic circuit design and digital signal processing. It is designed to provide the necessary electronic laboratory skills required to progress in either experimental physics research, or industrial R&D roles. The first half of the course covers linear network theory including sections on: Resonant matching networks, poles and zeros, Bode plots, the Laplace transform in network theory, feedback and oscillation, and active filters. The second half of the course introduces the basics of digital signal processing including: sampling theory, the Nyquist theorem, digital filters, the DFT and signal processing using the DFT.

Course Requirements

Prerequisite: 15 points from PHYSICS 240, 244 and 15 points from PHYSICS 211, MATHS 253, 260, ENGSCI 211 Concurrent enrolment in PHYSICS 390 is recommended Restriction: PHYSICS 341

Capabilities Developed in this Course

Capability 1: Disciplinary Knowledge and Practice
Capability 2: Critical Thinking
Capability 3: Solution Seeking
Capability 4: Communication and Engagement
Capability 5: Independence and Integrity
Graduate Profile: Bachelor of Science

Learning Outcomes

By the end of this course, students will be able to:
  1. Analyse simple electronic circuits to deduce their function (Capability 1 and 2)
  2. Demonstrate an understanding of basic linear network theory and apply this to practical circuits (Capability 1 and 2)
  3. Demonstrate an understanding of basic digital signal processing and sampling theory and apply this to real-world data sources. (Capability 1 and 2)
  4. Work within a team to apply the theoretical knowledge gained during to course to a experimental electronic design problem (Capability 1, 2, 3, 4 and 5)
  5. Demonstrate ability to present the key elements of your group's project work in a written report. (Capability 1, 4 and 5)

Assessments

Assessment Type Percentage Classification
Assignments 30% Individual Coursework
Project 20% Group & Individual Coursework
Final Exam 50% Individual Examination
Assessment Type Learning Outcome Addressed
1 2 3 4 5
Assignments
Project
Final Exam

The coursework will be assessed by four, equally weighted, fifty-minute, in-class assignments. You will be permitted to bring the course text, and any notes you wish, into the assignment room (30%), AND one group project assessed from two short written reports. This project will be carried out over 10 tutorial periods (ie in class time) in the advanced lab.

Learning Resources

The coursebook for this course is “Network Theory and Digital Signal Processing”, 3rd Edition, 2015  © Gary E.J. Bold.

This text is available from the student bookshop. This year it has an orange cover.

Numerical circuit simulations used will be based on LTSpice. Instructions on using LTSpice, and Spice programs in general, will be given in class. LTSpice IV has been installed on all Advanced Lab machines, it may also be downloaded for free from:

http://ltspice.linear.com/software/LTspiceIV.exe

Other simulations, and DSP related filtering work, will use Python and the scientific libraries NumPy and SciPy.

Special Requirements

Participation in the group project is compulsory.

Workload Expectations

This course is a standard 15 point course and students are expected to spend 10 hours per week involved in each 15 point course that they are enrolled in.

For this course, you can expect 22 hours of lectures, 10 one hour tutorials, 68 hours of reading and thinking about the content and 50 hours of work on assignments and/or test preparation.

Digital Resources

Course materials are made available in a learning and collaboration tool called Canvas which also includes reading lists and lecture recordings (where available).

Please remember that the recording of any class on a personal device requires the permission of the instructor.

Copyright

The content and delivery of content in this course are protected by copyright. Material belonging to others may have been used in this course and copied by and solely for the educational purposes of the University under license.

You may copy the course content for the purposes of private study or research, but you may not upload onto any third party site, make a further copy or sell, alter or further reproduce or distribute any part of the course content to another person.

Academic Integrity

The University of Auckland will not tolerate cheating, or assisting others to cheat, and views cheating in coursework as a serious academic offence. The work that a student submits for grading must be the student's own work, reflecting their learning. Where work from other sources is used, it must be properly acknowledged and referenced. This requirement also applies to sources on the internet. A student's assessed work may be reviewed against online source material using computerised detection mechanisms.

Inclusive Learning

All students are asked to discuss any impairment related requirements privately, face to face and/or in written form with the course coordinator, lecturer or tutor.

Student Disability Services also provides support for students with a wide range of impairments, both visible and invisible, to succeed and excel at the University. For more information and contact details, please visit the Student Disability Services’ website at http://disability.auckland.ac.nz

Special Circumstances

If your ability to complete assessed coursework is affected by illness or other personal circumstances outside of your control, contact a member of teaching staff as soon as possible before the assessment is due.

If your personal circumstances significantly affect your performance, or preparation, for an exam or eligible written test, refer to the University’s aegrotat or compassionate consideration page: https://www.auckland.ac.nz/en/students/academic-information/exams-and-final-results/during-exams/aegrotat-and-compassionate-consideration.html.

This should be done as soon as possible and no later than seven days after the affected test or exam date.

Student Feedback

During the course Class Representatives in each class can take feedback to the staff responsible for the course and staff-student consultative committees.

At the end of the course students will be invited to give feedback on the course and teaching through a tool called SET or Qualtrics. The lecturers and course co-ordinators will consider all feedback.

Your feedback helps to improve the course and its delivery for all students.

Student Charter and Responsibilities

The Student Charter assumes and acknowledges that students are active participants in the learning process and that they have responsibilities to the institution and the international community of scholars. The University expects that students will act at all times in a way that demonstrates respect for the rights of other students and staff so that the learning environment is both safe and productive. For further information visit Student Charter (https://www.auckland.ac.nz/en/students/forms-policies-and-guidelines/student-policies-and-guidelines/student-charter.html).

Disclaimer

Elements of this outline may be subject to change. The latest information about the course will be available for enrolled students in Canvas.

In this course you may be asked to submit your coursework assessments digitally. The University reserves the right to conduct scheduled tests and examinations for this course online or through the use of computers or other electronic devices. Where tests or examinations are conducted online remote invigilation arrangements may be used. The final decision on the completion mode for a test or examination, and remote invigilation arrangements where applicable, will be advised to students at least 10 days prior to the scheduled date of the assessment, or in the case of an examination when the examination timetable is published.

Published on 12/02/2020 08:13 p.m.