<meta http-equiv="refresh" content="0; URL=noscript.html"> METU | Course Syllabus

### 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.