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    Overview

    An introduction to the "systems" approach to solving physical problems: generalised functions, the Fourier transform, sampling and the FFT, causality and the Kramers-Kronig relations, noise processes and matched filtering.

    About this paper

    Paper title Linear Systems and Noise
    Subject Electronics
    EFTS 0.0833
    Points 10 points
    Teaching period Semester 1 (On campus)
    Domestic Tuition Fees ( NZD ) $685.39
    International Tuition Fees Tuition Fees for international students are elsewhere on this website.
    Limited to
    BSc(Hons), PGDipSci, MSc, MAppSc
    Contact

    ashton.bradley@otago.ac.nz

    Teaching staff

    Course Co-ordinator: Dr Ashton Bradley

    Textbooks

    Textbooks are not required for this paper.

    Graduate Attributes Emphasised
    Global perspective, Interdisciplinary perspective, Lifelong learning, Scholarship, Communication, Critical thinking, Information literacy, Self-motivation, Teamwork.
    View more information about Otago's graduate attributes.
    Learning Outcomes

    After completing this paper students are expected to:

    1. Have a good understanding of the delta function and generalised functions in general and be able to use the formal definition of generalised functions for doing calculus on generalised functions
    2. Understand the convolution integral and its relation to the delta function and the superposition principle
    3. Be familiar with the Fourier transform and its properties and be comfortable finding Fourier transforms using the properties of the Fourier transform and the Fourier transforms for a base set of functions
    4. Find the Fourier transform of generalised functions from the definition
    5. Understand sampling and its effects in the Fourier domain and be able to derive the sampling theorem and show the relationship between the discrete and continuous Fourier transforms
    6. Understand the effect of causality on a system transfer function, the Hilbert transform and the Kramers-Kronig relation
    7. Be able to solve problems related to the one dimensional propagation of a signal through a dispersive and for the narrow bandwidth approximation derive expressions for the group and phase velocities
    8. Be introduced to stationary stochastic processes and be able to calculate the effect of a linear system on the power spectrum of a signal
    9. Be able to use matched filtering to optimally find signals in noise

    Timetable

    Semester 1

    Location
    Dunedin
    Teaching method
    This paper is taught On Campus
    Learning management system
    None
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