MEE7027 INTELLIGENT COMPUTATION SYSTEMS

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Oct 23, 2013 (3 years and 10 months ago)

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MEE702
7


Thursday, October 24, 2013




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GRIFFITH UNIVERSITY

FACULTY OF ENGINEERING AND INFORMATION TECHNOLOGY

MEE
702
7

INTELLIGENT COMPUTATION SYSTEMS

SUBJECT OUTLINE


1.0

IDENTIFYING INFORMATION



Subject Code:


MEE
7027


Subject Title:


Intelligent Computation Systems


Faculty:


Engineering and
Information Technology


School:



Microelectronic Engineering


Discipline Code:

020199




Course/s for which subject is designed:



MEE401 Graduate Diploma of Computer and Information Engineering



MEE402 Graduate Diploma of Communications and Information
Engineering



MEE502 Master of Computer and Information Engineering



MEE503 Master of Communications and Information Engineering



Status of subject within course:

First or Second Semester Elective Subject (dependent upon
the semester in which a student c
ommences the program)


Credit Point Value:


10CP


Prerequisites:



Completion of Year 3 subjects in electronic/software
engineering programs, or Year 3 subjects in Information
Technology degree






or equivalents


Corequisites:



Nil


Prior Assumed:



Nil


Incompatible:



Nil


Year and Semester:


For Graduate Diploma Students: Year 1, Semester 2






For Masters Students: Year 1, Semester 2 or Year 2,
Semester 2


Year of Offer:



2001


Subject Convenor:


Dr Chi
-
Hsu Wang


Office Location:


T
EN
-
1.11


Offi
ce Telephone:


(07) 3875
5381


Email Address:



c.wang
@me.gu.edu.au


Teaching Team Members:

Dr Chi
-
Hsu Wang


2.0

OBJECTIVES


With the fast development of intelligent computation techniques over the past two decades, we
are witnessed with the enormous engin
eering applications out of the intelligent computation
techniques. The major objectives of this subject are to teach the students with the
fundamentals of intelligent computation techniques, such as fuzzy logic, neural network, and
genetic algorithms. Th
e engineering applications will also be explored, especially in the areas
of computer, communication, and control engineering. The content of this subject reflects both

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MEE702
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the fundamentals and engineering applications. It is a whole new concept for performi
ng
engineering applications. The students will meet future professional trends after taking this
subject.


3.0

BRIEF DESCRIPTION


This subject includes the fundamentals of intelligent computation techniques, such as fuzzy
logic, neural network, and geneti
c algorithms. The engineering applications will also be
explored, especially in the areas of computer, communication, and control engineering.


4.0

CONTENT


1.

Fuzzy Set and Fuzzy Logic

2.

Possibility Theory and Fuzzy Arithmetic

3.

Fuzzy Logic and Approximate Reas
oning

4.

Fuzzy Logic Control Systems

5.

Fuzzy Pattern Recognition

6.

Fuzzy Linear Programming

7.

Artificial Neural Network

8.

Feedforward Networks and Supervised Learning

9.

Unsupervised Learning Networks

10.

Universal Approximation Theorem

11.

Fuzzy Neural Networks (FNNs)

12.

Genetic
Algorithms (GAs)

13.

Adaptive Fuzzy Neural Networks

with Real
-
Time Applications

14.

Engineering Applications


5.0

ORGANISATION AND TEACHING METHODS


1.

Two hours of lecture per week. Twenty eight hours of lectures per semester;

2.

Powerpoint presentation using notebook

computer will be adopted during the lecture;

3.

Four hours of laboratory per week. Fifty six hours of laboratory per semester;

4.

The students must do their assignments and projects during laboratory hours;

5.

Matlab 6.0 with Fuzzy, Neural Network and Control too
lboxes will be installed in the
laboratory for assignments;

6.

The Matlab real
-
time toolbox with hardware development tools will be provided in the
laboratory for project work.


6.0

ASSESSMENT


Five Assignments:

30%

Project:



30%

Final Examination:

40%


7.0

TEXTS AND SUPPORTING MATERIALS


1.

“Neural Fuzzy Systems: A Neural
-
Fuzzy Synergism to Intelligent Systems”, C. T. Lin and
C. S. George Lee, Prentice Hall, 1996.

2.

“A Course in Fuzzy Systems and Control”, Li
-
Xin Wang, Prentice Hall, 1997.

3.

Relevant research arti
cles from IEEE Transactions on Fuzzy Systems; IEEE Transactions
on Neural Networks; IEEE Transactions on Systems, Man, and Cybernetics, …, etc



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8.0

ADMINISTRATION


8.1

The Subject Convenor will administer the subject through the School of
Microelectronic E
ngineering.


8.2

Prerequisite/Prior Assumed Requirements

Enrolment in this subject is granted on the basis that a grade of Pass (P) or better has
been achieved in any prerequisite or prior assumed requirement in this subject as listed
under Section 1 of th
is outline. Failure to meet this requirement may result in you
having difficulty with the subject and not being able to complete it successfully.
Any
additional support or special assistance cannot be expected, nor requested, if
the prerequisite and/or p
rior assumed requirements have not been met.




Signed:














Subject Convenor






Date



Signed:














Head of School, School of Microelectronic Engineering


Date



Signed:














Chair, Faculty Board






Date