CSE301留学生代写、MATLAB程序语言调试、代写MATLAB代写、MLP代做

日期：2019-12-19 11:05

CSE301 – Bio-Computation Assessment 3

Contribution to overall module assessment 10%

Submission deadline 18:00, Friday, Dec 20 2019

1. Assessment Task

In this assessment, you are to implement MLP with back-propagation training algorithm, and RBF

network with the RBF centers initialized from k-means clustering, using MATLAB for vehicle logo

classification. Please use sigmoid activation functions where necessary.

In the dataset (logo.mat), 117 samples of 5 different types of vehicle logo images as shown in Fig. 1

are provided, with corresponding class labels (1-5) and 80 features in each sample using appropriate

feature extraction algorithm.

Fig.1 Examples of vehicle logo images

For both MLP and RBF design, divide the dataset into a training set (80%) and a testing set (20%) and

show the convergence performance using MSE for each epoch in the training process.

Based on your algorithms designed, discuss the following in the report:

(1) for MLP: the effect of different number of hidden units;

(2) for MLP: the effect of different learning rate and momentum;

(3) for RBF: the effect of different number of RBF centres;

(4) compare the best MLP model and the best RBF model using confusion matrix.

Note:

(1) it is acceptable to follow references (or using code fragments) from textbooks or internet

resources, but you must cite them clearly in your report;

(2) it is acceptable to apply Matlab toolboxes and Matlab functions.

2. Report

Each student must write an individual report in English. The report must be a single file in .pdf format

including all the plots, figures, tables and appendixes (failure to comply with this requirement will be

marked as Fail according 5. Marking Criteria).

The format of the report is: single-column A4 size, Times New Roman 12pt, single line spacing, page

numbered, 0.75-inch margin on top/bottom/left/right, and with maximum 10 pages including cover

page, reference (and appendixes if any).

The structure of the report is:

(1) introduction: task description and background;

(2) methodology: introduction of the methods and models;

(3) experimental results and analysis: experiment procedures, results discussion and analysis,

performance comparison etc.;

(4) conclusion;

(5) references.

3. Submission

You are required to:

(1) compress your written report and source code into one single .ZIP file (other format such as .rar

or .7z will be marked as Fail according to 5. Marking Criteria);

(2) name the zip file as: StudentID_GivenName_Surname (e.g. 1601234_Rui_Yang);

(3) upload to the submission folder in ICE by 18:00, Friday, Dec 20 2019.

Late submission will receive penalty in the marking in accordance with the University Code of Practice

on Assessment. For each working day after the deadline, 5 marks (out of 100) will be deducted for up

to 5 working days. However, the mark will not be reduced below the pass mark for the assessment.

Work assessed below the pass mark will not be penalised for late submission of up to 5 days. Work

received more than 5 working days after the deadline will receive a mark of 0.

4. Plagiarism

This assessment is an individual work. Plagiarism (e.g. copying materials from other sources without

proper acknowledgement) is a serious academic offence. Plagiarism will not be tolerated and will be

dealt with in accordance with the University Code of Practice on Assessment.

5. Marking Criteria

Category Requirement

First Class

(≥70%)

Overall outstanding work. All of the requirements have been implemented in the

program and report. Highly qualified report that closes to professional level. The

report is well-structured and organized, with all of required information included,

with very few English problems.

Second Upper

(60 to 69%)

Most of the requirements have been implemented in the program and report.

Good report which is clearly structured with most of the required information but

with few English problems.

Second Lower

(50 to 59%)

Substantial working program implementing a good range of the requirements.

Acceptable written report for Year 4 level, which contains sufficient information

but some English problems.

Third

(40 to 49%)

Executable program that generates recognizable results, which however are

incomplete. The written report is readable with insufficient information covered.

Problems may appear in the structure and organization, with many English

problems.

Fail

(0 to 39%)

Wrong format in submission. Program is not working; or most of the required

results are not produced; or without acknowledging properly sources used if any.

Poor report which covers very limited number of items required.

No submission A mark of 0 will be awarded.

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