Review of linear discrete-time systems and sampled and discrete-time signals; Fourier analysis, discrete and fast Fourier transforms; interpolation and decimation; design of infinite-impulse response and finite impulse response filters. introduction to real time processing using Digital Signal Processors (DSP) chips.
Discrete-Time Signals and Systems (EE 312)
2024 Spring
Faculty of Engineering and Natural Sciences
Electronics Engineering(EE)
3
6
Çağlar Tunç caglar.tunc@sabanciuniv.edu,
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English
Undergraduate
ENS211
Formal lecture,Recitation,Laboratory
Interactive,Communicative,Project based learning,Simulation
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| Programs\Type | Required | Core Elective | Area Elective |
| Computer Science and Engineering | * | ||
| Computer Science and Engineering | * | ||
| Electronics Engineering | * | ||
| Electronics Engineering | * | ||
| Materials Science and Nano Engineering | * | ||
| Materials Science and Nano Engineering (Previous Name: Materials Science and Engineering) | * | ||
| Mechatronics Engineering | * | ||
| Mechatronics Engineering | * | ||
| Microelectronics | * | ||
| Molecular Biology, Genetics and Bioengineering | * | ||
| Molecular Biology, Genetics and Bioengineering (Pre. Name: Biological Sciences and Bioengineering) | * | ||
| Telecommunications | * |
CONTENT
OBJECTIVE
To provide students fundamentals of signal processing in discrete-time and enable them to develop the background for graduate level studies such as adaptive filtering. To provide students knowledge of algorithm design, implementation and analysis through comprehensive experiments/simulations in MATLAB during laboratory sessions.
LEARNING OUTCOMES
- At the end of the course, the student is expected to have the ability to construct mathematical models of real life problems and use appropriate methods/software to implement.
- At the end of the course, the student is expected to have learned sampling, and also expected to have the ability to understand and analyze the effect of sampling in the signal level as well as the system level in both time domain and frequency domain.
- At the end of the course, the student is expected to have the ability to understand and analyze the discrete-time signals and systems in both time domain and frequency domain.
- At the end of the course, the student is expected to have the ability to understand and analyze the discrete-time signals and systems in frequency domain through Discrete Fourier Transform (as an example of finite length discrete transforms).
- At the end of the course, the student is expected to have achieved a deeper understanding and the ability of conducting a deeper analysis of discrete-time signals and systems through z-transform
- At the end of the course, the student is expected to have the ability to recognize and analyze FIR and IIR filters, and to have achieved a solid understanding of their advantages and disadvantages.
- At the end of the course, the student is expected to have learned the fundamentals of IIR (infinite impulse response) filter design and to use Matlab to design IIR filters.
- At the end of the course, the student is expected to have learned the fundamentals of FIR (finite impulse response) filter design and to use Matlab to design FIR filters.
PROGRAMME OUTCOMES
1. Understand the world, their country, their society, as well as themselves and have awareness of ethical problems, social rights, values and responsibility to the self and to others. 2
2. Understand different disciplines from natural and social sciences to mathematics and art, and develop interdisciplinary approaches in thinking and practice. 2
3. Think critically, follow innovations and developments in science and technology, demonstrate personal and organizational entrepreneurship and engage in life-long learning in various subjects; have the ability to continue to educate him/herself. 4
4. Communicate effectively in Turkish and English by oral, written, graphical and technological means. 3
5. Take individual and team responsibility, function effectively and respectively as an individual and a member or a leader of a team; and have the skills to work effectively in multi-disciplinary teams. 4
1. Possess sufficient knowledge of mathematics, science, fundamental engineering, computational methods and program-specific engineering topics; use theoretical and applied knowledge of these areas in complex engineering problems. 5
2. Identify, define, formulate and solve complex engineering problems while considering the UN Sustainable Development Goals; choose and apply suitable analysis, design, estimation/prediction and modeling methods for this purpose. 5
3. Develop, choose and use modern techniques and tools that are needed for analysis and solution of complex problems faced in engineering applications; use information technologies effectively. 4
4. Have the ability to design a complex system, process, instrument or a product under realistic constraints and conditions, with the goal of fulfilling creative current and future requirements. 5
5. Use research methods, including conducting literature reviews, designing experiments, performing experiments, collecting data, analyzing results, and interpreting results, to investigate complex engineering problems or discipline-specific research topics. 4
6. Possess knowledge of business practices such as project management, risk management, change management, and economic feasibility analysis; awareness on entrepreneurship and innovation. 1
7. Possess knowledge of impact of engineering solutions on society, health and safety, the economy, sustainability, and the environment within the framework of the UN Sustainable Development Goals; awareness on legal outcomes of engineering solutions; awareness of acting impartially and inclusively without any form of discrimination; act in accordance with ethical principles, possessing knowledge of professional and ethical responsibilities. 2
8. Communicate effectively, both orally and in writing, on technical subjects, considering the diverse characteristics of the target audience (such as education, language, and profession). 5
Update Date:
ASSESSMENT METHODS and CRITERIA
| Percentage (%) | |
| Final | 30 |
| Quiz | 30 |
| Participation | 15 |
| Group Project | 25 |
RECOMENDED or REQUIRED READINGS
| Textbook |
1) (required) Digital Signal Processing, A computer based approach 4th edition, Sanjit K. Mitra, McGraw Hill, 2006, 007-124467-0 |