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)
2020 Spring
Faculty of Engineering and Natural Sciences
Electronics Engineering(EE)
3
6
Hüseyin Özkan hozkan@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 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; choose and apply suitable analysis 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; possess knowledge of standards used 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 specified needs; apply modern design techniques for this purpose. 5
5. Design and conduct experiments, collect data, analyze and interpret the results to investigate complex engineering problems or program-specific research areas. 4
6. Possess knowledge of business practices such as project management, risk management and change management; awareness on innovation; knowledge of sustainable development. 1
7. Possess knowledge of impact of engineering solutions in a global, economic, environmental, health and societal context; knowledge of contemporary issues; awareness on legal outcomes of engineering solutions; knowledge of behavior according to ethical principles, understanding of professional and ethical responsibility. 2
8. Have the ability to write effective reports and comprehend written reports, prepare design and production reports, make effective presentations, and give and receive clear and intelligible instructions. 5
1. Comprehend key concepts in biology and physiology, with emphasis on molecular genetics, biochemistry and molecular and cell biology as well as advanced mathematics and statistics. 1
2. Develop conceptual background for interfacing of biology with engineering for a professional awareness of contemporary biological research questions and the experimental and theoretical methods used to address them. 1
1. Design, implement, test, and evaluate a computer system, component, or algorithm to meet desired needs and to solve a computational problem. 2
2. Demonstrate knowledge of discrete mathematics and data structures. 3
3. Demonstrate knowledge of probability and statistics, including applications appropriate to computer science and engineering. 1
1. Use mathematics (including derivative and integral calculations, probability and statistics, differential equations, linear algebra, complex variables and discrete mathematics), basic sciences, computer and programming, and electronics engineering knowledge to (a) Design and analyze complex electronic circuits, instruments, software and electronics systems with hardware/software or (b) Design and analyze communication networks and systems, signal processing algorithms or software 5
1. Applying fundamental and advanced knowledge of natural sciences as well as engineering principles to develop and design new materials and establish the relation between internal structure and physical properties using experimental, computational and theoretical tools. 1
2. Merging the existing knowledge on physical properties, design limits and fabrication methods in materials selection for a particular application or to resolve material performance related problems. 1
3. Predicting and understanding the behavior of a material under use in a specific environment knowing the internal structure or vice versa. 1
1. Familiarity with concepts in statistics and optimization, knowledge in basic differential and integral calculus, linear algebra, differential equations, complex variables, multi-variable calculus, as well as physics and computer science, and ability to use this knowledge in modeling, design and analysis of complex dynamical systems containing hardware and software components. 4
2. Ability to work in design, implementation and integration of engineering applications, such as electronic, mechanical, electromechanical, control and computer systems that contain software and hardware components, including sensors, actuators and controllers. 5
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ASSESSMENT METHODS and CRITERIA
| Percentage (%) | |
| Final | 25 |
| Midterm | 40 |
| Quiz | 10 |
| Assignment | 10 |
| Group Project | 15 |
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 |