Introduction to Digital Signal Processing

Course Code:

EE 361

Course Period:

Autumn

Course Type:

Core

Credits:

4

Theoric:

3

Practice:

0

Laboratory Hour:

2

ECTS:

7

Course Language:

English

Courses given by:

İpek Baz

Course Assistants :

Caner Toprak

Course Content:

The aim of this course is to introduce students to discrete and continuous signals and systems. This course also prepares the background for compulsory courses in communication and control systems.

Course Methodology:

1: Lecture by instructor, 2: Lecture by instructor with class discussion, 3: Problem solving by instructor, 4: Use of simulations, 5: Problem solving assignment, 6: Reading assignment, 7: Laboratory work, 8: Term research paper, 9: Presentation by guest s

Course Evaluation Methods:

A: Written exam, B: Multiple-choice exam C: Take-home quiz, D: Experiment report, E: Homework, F: Project, G: Presentation by student

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Course Learning Outcomes

Course Learning Outcomes	Detailed Program Outcomes	Teaching Methods	Assessment Methods
1) Ability to define and remember mathematical concepts related to continuous and discrete signals	1a	1,3,5	A,C
2) Ability to describe the methodology to generate sinusoidal signals	2a,2b	1,3,5	A,C
3) Ability to implement the described methodology to create sinusoidal signals in laboratory (examine the results)	5b,7c	7	D
4) Ability to identify the appropriate methodology for spectral representation	2a,2b	1,3,5	A,C
5) Ability to implement the identified methodology for spectral representation in laboratory (examine the results)	5b,7c	7	D
6) Ability to select the methodology for sampling	2a,2b	1,3,5	A,C
7) Ability to implement the selected methodology for sampling in laboratory (examine the results)	5b,7c	7	D
8) Ability to locate the methods to implement FIR filters and IIR filters	2a,2b	1,3,5	A,C
9) Ability to implement the selected methods to create FIR filters and IIR filters in laboratory (examine the results)	5b,7c	7	D
10) Ability to identify methods to construct Fourier and Z-transforms	2a,2b	1,3,5	A,C
11) Ability to implement the identified methods to create Fourier and Z-transforms in laboratory (examine the results)	5b,7c	7	D

Course Flow

COURSE CONTENT
Week	Topics	Study Materials
1	Introduction to Signal Processing	Chapter 1 - http://dspfirst.gatech.edu/
2	Sinusoids	Chapter 2 - http://dspfirst.gatech.edu/
3	Spectrum Representation	Chapter 3 - http://dspfirst.gatech.edu/
4	Spectrum Representation	Chapter 3 - http://dspfirst.gatech.edu/
5	Sampling	Chapter 4 - http://dspfirst.gatech.edu/
6	Sampling	Chapter 4 - http://dspfirst.gatech.edu/
7	Midterm I	-
8	FIR Filters	Chapter 5- http://dspfirst.gatech.edu/
9	FIR Filters	Chapter 5- http://dspfirst.gatech.edu/
10	Frequency Response of FIR Filters	Chapter 6- http://dspfirst.gatech.edu/
11	Fourier Transform	Related videos on web
12	Midterm II	-
13	Discrete Time Fourier Transform	Chapter 7 ve Chapter 8- http://dspfirst.gatech.edu/
14	Z- Transform and IIR Filters	Chapter 9 ve Chapter 10 http://dspfirst.gatech.edu/

Recommended Sources

RECOMMENDED SOURCES
Textbook	DSP First, 2nd Edition; J. H. McClelland, R. W. Schafer, M. A. Yoder; Prentice Hall Inc., 2016.
Additional Resources	Digital Signal Processing, 4th Edition, John G. Proakis, Prentice Hall Inc., 2007. Signals and Systems; A. V. Oppenheim, A. S. Willsky, with S. H. Nawab; Prentice Hall Inc.; Second Edition; ISBN: 0138147574. Student Edition of Matlab.

Material Sharing

MATERIAL SHARING
Documents	Various scientific publications, supplementary notes and lecture videos on the web
Laboratory	Laboratory Manual
Exams	Exam questions and answers

Assessment

ASSESSMENT
IN-TERM STUDIES	NUMBER	PERCENTAGE
Midterms	2	30
Homeworks	5	15
Final Exam	1	30
Laboratory	7	25
Total	15	100
CONTRIBUTION OF FINAL EXAMINATION TO OVERALL GRADE	1	30
CONTRIBUTION OF IN-TERM STUDIES TO OVERALL GRADE	14	70
Total		100

Course’s Contribution to Program

COURSE'S CONTRIBUTION TO PROGRAM OUTCOMES
No	Program Learning Outcomes	check √
1a	Adequate knowledge in mathematics, science and engineering subjects pertaining to the relevant discipline,	√
1b	Ability to use theoretical and applied knowledge in these areas in complex engineering problems.
2a	Ability to identify, formulate, and solve complex engineering problems,	√
2b	Ability to select and apply proper analysis and modeling methods for this purpose.	√
3a	Ability to design a complex system, process, device or product under realistic constraints and conditions, in such a way as to meet the desired result,
3b	Ability to apply modern design methods for this purpose.
4a	Ability to devise, select and use modern techniques and tools needed for analyzing and solving complex problems encountered in engineering practice.
4b	Ability to employ information technologies effectively.
5a	Ability to design experiments for investigating complex engineering problems or discipline specific research questions,
5b	Ability to conduct experiments, gather data, analyze and interpret results for investigating complex engineering problems or discipline specific research questions.	√
6a	Ability to work efficiently in intra-disciplinary teams,
6b	Ability to work efficiently in multi-disciplinary teams,
6c	Ability to work individually.
7a	Ability to communicate effectively in Turkish, both orally and in writing,
7b	Knowledge of a minimum of one foreign language,
7c	Ability to write effective reports and comprehend written reports, prepare design and production reports,	√
7d	Ability to make effective presentations,
7e	Ability to give and receive clear and intelligible instructions.
8a	Recognition of the need for lifelong learning, ability to access information, ability to follow developments in science and technology,
8b	Ability to continue to educate him/herself.
9a	Consciousness to behave according to ethical principles and professional and ethical responsibility.
9b	Knowledge on standards used in engineering practice.
10a	Knowledge about business life practices such as project management, risk management, change management.
10b	Awareness in entrepreneurship and innovation.
10c	Knowledge about sustainable development.
11a	Knowledge about the global and social effects of engineering practices on health, environment, and safety,
11b	Knowledge about contemporary issues of the century reflected into the field of engineering.
11c	Awareness of the legal consequences of engineering solutions.

ECTS

ECTS ALLOCATED BASED ON STUDENT WORKLOAD BY THE COURSE DESCRIPTION
Activities	Quantity	Duration (Hour)	Total Workload (Hour)
Course Duration	14	3	42
Hours for off-the-classroom study (Pre-study, practice)	15	6	90
Midterms	2	2	4
Laboratory	7	2	14
Homeworks	5	3	15
Final	1	2	2
Total Work Load			167
Total Work Load / 25 (h)			6,68
ECTS Credit of the Course			7

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Introduction to Digital Signal Processing

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