EE430 DIGITAL SIGNAL PROCESSING

Course Code:5670430
METU Credit (Theoretical-Laboratory hours/week):3 (3.00 - 0.00)
ECTS Credit:5.0
Department:Electrical and Electronics Engineering
Language of Instruction:English
Level of Study:Undergraduate
Course Coordinator:Prof.Dr. ABDULLAH AYDIN ALATAN
Offered Semester:Fall or Spring Semesters.

Course Objectives

Course Objective 1: Students will be able to demonstrate their understanding of fundamental discrete-time signal and system concepts.

Course Objective 2: Students will be able to interpret Fourier analysis of periodic and aperiodic discrete-time signals with an extension to z-transform.

Course Objective 3: Students will be able to understand sampling, reconstruction and rate conversion concepts for sequences and analyze such systems with processing modules.

Course Objective 4: Students will be able to interpret transform domain behavior of discrete-time systems with emphasis on their frequency response.

Course Objective 5: Students will be able to formulate a solution for designing discrete-time filters based on some constraints using different structures.

 


Course Content

Discrete-time signals and systems. Discrete Fourier transform. Sampling and reconstruction. Linear time-invariant systems. Structures for discrete-time systems. Filter design techniques. Fast Fourier Transform methods. Fourier analysis of signals using discrete Fourier transform. Optimal filtering and linear prediction.


Course Learning Outcomes

1.1 Differentiate between various types of discrete-time (DT) systems and sequences. 

1.2 Characterize and utilize eigenproperty of  DT linear time-invariant (LTI) systems.

1.3 Compute convolution for DT LTI systems. 

1.4  Determine the impulse response of a DT LTI system represented by an LCCDE.

 

2.1 Determine the discrete-time Fourier Transform (DTFT) of a sequence.

2.2 Represent a periodic  sequence through discrete Fourier series (DFS).

2.3 Characterize the relation of Discrete Fourier Transform (DFT) to DFS and DTFT.

2.4  Compare z-transform with DTFT and explain region of convergence.

2.5  Compute (linear) convolution by using DFT.

2.6 Compute DFT in a computationally efficient manner 

 

3.1 Describe the mathematical model of sampling and reconstruction, indicating the frequency behavior and its limits.

3.2 Analyze a signal processing system that contains sampling and reconstruction stages. 

3.3 Construct rate-conversion systems to reach a desired rate and frequency response.    

3.4 Describe practical issues in sampling  & reconstruction

 

4.1 Determine the frequency response (magnitude and phase) of DT systems from its poles and zeros.

4.2 Characterize the properties of minimum-phase, all-pass and linear phase systems.

 

5.1 Apply filter design techniques based on a set of constraints on frequency response

5.2 Construct different representations of the same DT system.


Program Outcomes Matrix

Contribution
#Program OutcomesNoYes
1An ability to identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics
2An ability to apply engineering design to produce solutions that meet specified needs with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors
3An ability to communicate effectively with a range of audiences
4An ability to recognize ethical and professional responsibilities in engineering situations and make informed judgments, which must consider the impact of engineering solutions in global, economic, environmental, and societal contexts.
5An ability to function effectively on a team whose members together provide leadership, create a collaborative and inclusive environment, establish goals, plan tasks, and meet objectives
6An ability to develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions
7An ability to acquire and apply new knowledge as needed, using appropriate learning strategies