• Basic information
• Learning outcomes
• Contents
• Assessment
• Workload

Learning outcomes

Upon successful completion of this course, students will be able to:

1. Understand analogue/digital conversion as required for the digital processing of analogue signals.

   Contribution to Program Outcomes

   1. Obtain basic knowledge of Electronics Engineering.
   2. Formulate and solve engineering problems

   Method of assessment

   1. Written exam
   2. Homework assignment
2. Familiarity with fundamental concepts such as 'linearity' , 'time-invariance', 'impulse response', 'convolution', 'frequency response', 'z-transforms' and the 'discrete time Fourier transform'. as applied to signal processing systems.

   Contribution to Program Outcomes

   1. Obtain basic knowledge of Electronics Engineering.

   Method of assessment

   1. Written exam
3. Perform frequency domain analysis of discrete-time systems using Z-transform and discrete Fourier transform techniques.

   Contribution to Program Outcomes

   1. Formulate and solve engineering problems

   Method of assessment

   1. Written exam
   2. Homework assignment
4. Process digital signals using Fourier transforms and the z-transform.

   Contribution to Program Outcomes

   1. Formulate and solve engineering problems

   Method of assessment

   1. Written exam

Contents
Week 1:	Discrete-time signals
Week 2:	Discrete-time systems
Week 3:	LTI systems, properties of LT systems
Week 4:	Frequency-domain representation of discrete-time signals and systems, discrete-time Fourier series and properties
Week 5:	Discrete-time Fourier transform and properties, filtering
Week 6:	Discrete-time random signals
Week 7:	Discrete-Fourier series, general review
Week 8:	The frequency response of LTI systems, Midterm Exam
Week 9:	Discrete Fourier Transform and properties
Week 10:	Fast Fourier transform algorithms
Week 11:	Z-transform and z-transform properties
Week 12:	Inverse z-transform
Week 13:	Periodic sampling, frequency-domain representation of sampling, pre-filtering to avoid alising
Week 14:	Discrete-time processing of continuous-time signals
Week 15*:	.
Week 16*:	Final exam
Textbooks and materials:	A.V. Oppenheim and R.W. Schafer, Discrete Time Signal Processing, Prentice Hall, 2010
Recommended readings:	1.S. Mitra, Digital Signal Processing: A Computer-Based Approach, McGraw-Hill, 4. Edition, 2011 2. Signals and Systems by Alan V. Oppenheim, Alan S. Willsky, Hamid Nawab, Prentice Hall 1996 3. J. H. McClellan, R. W. Schafer, M. A. Yoder, Signal Processing First, Prentice Hall, 2003 4. J.G. Proakis and D.G. Manolakis, Digital Signal Processing: Principles, Algorithms, and Applications, Prentice-Hall, NJ, Fourth Edition, 2007 5. Vinay K. Ingle, John G. Proakis, Digital Signal Processing Using MATLAB, Thomson Learning, 2. Edition, 2006 6. M. Hayes, Schaum's Outline of Digital Signal Processing, McGraw-Hill, 1999
	* Between 15th and 16th weeks is there a free week for students to prepare for final exam.

Assessment
Method of assessment	Week number	Weight (%)
Mid-terms:	8	35
Other in-term studies:		0
Project:		0
Homework:	1,2,3,4,5	5
Quiz:	3,6	20
Final exam:	16	40
	Total weight:	(%)

Workload
Activity	Duration (Hours per week)	Total number of weeks	Total hours in term
Courses (Face-to-face teaching):	3	14
Own studies outside class:	3	14
Practice, Recitation:	0	0
Homework:	3	5
Term project:	0	0
Term project presentation:	0	0
Quiz:	0.25	2
Own study for mid-term exam:	10	1
Mid-term:	1.5	1
Personal studies for final exam:	12	1
Final exam:	2	1
		Total workload:
		Total ECTS credits:	*
	* ECTS credit is calculated by dividing total workload by 25. (1 ECTS = 25 work hours)