ITEE Home » ENGG7302 - Advanced Computational Techniques In Engineering » Material: ENGG7302

Print version

The University of Queensland
School of Information Technology and Electrical Engineering
Semester 2, 2009

ENGG7302 - Advanced Computational Techniques in Engineering

Course Material

Lecture Notes

Numerical Linear Algebra

1. Matrix-Vector Multiplication.
2. Orthogonal Vectors and Matrices.
3. Norms.
4. The Singular Value Decomposition.
5. More on the SVD.
6. Projection Matrices.
7. QR Decomposition.
8. Householder Triangularisation.
9. Least Squares Problems.
   

Stochastic Processes

1. Probability.
2. Random Variables.
3. Multiple Random Variables.
4. Introduction to Stochastic Processes.
5. Power Spectral Density.
6. Discrete-time Stochastic Processes.
7. Markov Chains.
   
8. Markov chain Monte Carlo.
   

Optimisation

1. Classical Mathematical and Numerical Optimization
2. Global Optimization and Metaheuristics
3. Evolutionary Computation
4. Swarm Intelligence
5. Simulated Annealing

Assignments and Tutorials

Assignments

• DUE 5pm, Monday, 7/9/09: Assignment 1
• digits.mat
• DUE 4pm, Monday, 12/10/09: Assignment 2
• DUE 4pm, Friday, 30/10/09: Assignment 3

Tutorials

• Weeks 2–3: Tutorial LA1
• Weeks 3–4: Tutorial LA2
• Weeks 4–5: Tutorial LA3
• Weeks 6–7: Tutorial SP1
• Weeks 7–8: Tutorial SP2
• Week 8: Tutorial SP3
• Weeks 9-10: Tutorial SP4
• Week 11: Tutorial OP1

Exams

Past Exams

• Semester 1, 2007: Class Test 2 (Stochastic Processes)
• Semester 1, 2007: Class Test 1 (Optimization)
• Semester 1, 2007: Final Exam
• Semester 2, 2007: Class Test 1 (Linear Algebra)
• Semester 2, 2007: Class Test 2 (Stochastic Processes)
• Semester 2, 2007: Final Exam
• Semester 1, 2008: Class Test 1 (Linear Algebra)
  
• Semester 1, 2008: Class Test 2 (Stochastic Processes)
• Semester 1, 2008: Final Exam
• Semester 2, 2008: Class Test 1 (Linear Algebra)
• Semester 2, 2008: Class Test 2 (Stochastic Processes)
• Semester 2, 2008: Final Exam
• Semester 1, 2009: Class Test 1 (Linear Algebra)
• Semester 1, 2009: Class Test 2 (Stochastic Processes)
• Semester 1, 2009: Final Exam
  
• Semester 2, 2009: Class Test 1 (Linear Algebra)
  

Reference Texts

• Lloyd N. Trefethen & David Bau, III, Numerical Linear Algebra, SIAM, 1997.
• Athanasios Papoulis & S. Unnikirshna Pillai, Probability, Random Variables and Stochastic Processes, McGraw-Hill, 4th ed., 2002.
  
• C. M. Grinstead and J. L. Snell. Introduction to Probability (Ch. 11). Available Online
• M. T. Heath. Scientific Computing: An Introductory Survey (Ch. 6 available online from library).

Additional Reference Texts

• D. Mackay. Information Theory, Inference, and Learning Algorithms. Oxford, 2003 (see Chap.29 for MCMC).
• S. Boyd and L. Vandenberghe. Convex Optimization.
• J. C. Spall. Introduction to Stochastic Search and Optimization: Estimation, Simulation and Control. Wiley, 2003.

Reference Material

• Paper: C. Andrieu, N. De Freitas, A. Doucet and M. I. Jordan. An Introduction to MCMC for Machine Learning. Machine Learning, 50, 5-43, 2003.
• Laird Breyer's MCMC web pages (including demo applet).
• Paper: J. R. Shewchuk. An Introduction to the Conjugate Gradient Method Without the Agonizing Pain. Tech Rept. School of Computer Science, Carnegie-Mellon University, 1994.
• Paper: C. Blum and A. Roli. Metaheuristics in Combinatorial Optimization: Overview and Conceptual Comparison. ACM Computing Surveys, Vol. 35, No. 3, September 2003, pp. 268-308.
• Simulated Annealing TSP Applet.
• 1-D continuous problem simulated annealing applet.
• Ant colony optimization TSP applet.
• Particle Swarm Optimization applet.
• Another Particle Swarm Optimization applet.
• Introduction to Probability Models, by Em Prof Tom Downs.
• Matlab primer (An Introduction to Matlab for Cognitive Programming) by Scott Bolland.

---