Module Specification
The information contained in this module specification was correct at the time of publication but may be subject to change, either during the session because of unforeseen circumstances, or following review of the module at the end of the session. Queries about the module should be directed to the member of staff with responsibility for the module.
Title NEURAL NETWORKS
Code ELEC320
Coordinator Dr JYI Goulermas
Computer Science
J.Y.Goulermas@liverpool.ac.uk
Year CATS Level Semester CATS Value
Session 2018-19 Level 6 FHEQ Second Semester 7.5

Aims
  • Understand the basic structures and the learning mechanisms underlying neural networks within the field of artificial intelligence and examine how synaptic adaptation can facilitate learning and how input to output mapping can be performed by neural networks.
  • Obtain an overview of linear, nonlinear, separable and non separable classification as well as supervised and unsupervised machine learning.
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    Pre-requisites before taking this module (other modules and/or general educational/academic requirements):
    MATH191OR; ELEC191; AND; MATH192OR; ELEC192  

    Co-requisite modules:
     

    Learning Outcomes
    Learning  the advantages and main characteristics of neural networks in relation to traditional methodologies. Also, familiarity with different neural networks structures and their learning mechanisms.
    Understanding of the neural network learning processes and their most popular types, as well as  appreciation of how neural networks can be applied to artificial intelligence problems.

    Syllabus
    1  12 lectures delivering the following chapters:
    • Introduction: Chapter 1
    • Structural Aspects: Chapter 2
    • Learning Processes: Chapter 3
    • Single-Layer Perceptrons: Chapter 4
    • Multi-Layer Perceptrons: Chapter 5
    • Radial-basis Function Networks: Chapter 6
    • Support Vector Machines: Chapter 7
    • Self-Organising Maps: Chapter 8

    Teaching and Learning Strategies

    Lecture -

    Tutorial -


    Teaching Schedule
      Lectures Seminars Tutorials Lab Practicals Fieldwork Placement Other TOTAL
    Study Hours 12

    		   6

    		       18
    Timetable (if known)              
    Private Study 57
    TOTAL HOURS 75

    Assessment
    EXAM Duration Timing
    (Semester)    		 % of
    final
    mark    		 Resit/resubmission
    opportunity    		 Penalty for late
    submission    		 Notes
    Unseen Written Exam  2 hours  Semester 2 examination period  100  No reassessment opportunity  Standard UoL penalty applies  Assessment 1 There is no reassessment opportunity, Notes (applying to all assessments) Formal exam  
    CONTINUOUS Duration Timing
    (Semester)    		 % of
    final
    mark    		 Resit/resubmission
    opportunity    		 Penalty for late
    submission    		 Notes
                 

    Reading List
    Reading lists are managed at readinglists.liverpool.ac.uk. Click here to access the reading lists for this module.
    Explanation of Reading List: