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| EHM3009 | Numerical Analysis | 3+0+0 | ECTS:4 | | Year / Semester | Fall Semester | | Level of Course | First Cycle | | Status | Compulsory | | Department | DEPARTMENT of ELECTRONICS and COMMUNICATION ENGINEERING | | Prerequisites and co-requisites | DC must have been achieved from EHM2004-Signals and Systems | | Mode of Delivery | | | Contact Hours | 14 weeks - 3 hours of lectures per week | | Lecturer | Dr. Öğr. Üyesi Emin TUĞCU | | Co-Lecturer | | | Language of instruction | Turkish | | Professional practise ( internship ) | None | | | | The aim of the course: | | The aim of this course is to introduce digital signal processing techniques and applications. After describing discrete-time signals and system properties, signal analysis tools in the frequency domain will be examined, discrete-time processing of continuous-time signals, z-transform, frequency domain analysis of linear and time-invariant systems, and digital filter design techniques will be covered. After taking this course, students are expected to have a basic understanding and knowledge in the transformation region analysis of discrete signals and systems. |
| Learning Outcomes | CTPO | TOA | | Upon successful completion of the course, the students will be able to : | | | | LO - 1 : | To be able to apply theoretical and applied knowledge in modeling and solving engineering problems in digital signal processing. | 1,2,4,5 | 1, | | LO - 2 : | To be able to identify, define, formulate and solve complex engineering problems encountered in the field of digital signal processing by choosing appropriate analysis and modeling methods. | 1,2,4,5 | 1, | | LO - 3 : | To be able to design a complex system and process encountered in the field of digital signal processing by applying modern design methods under realistic constraints and conditions. | 1,2,4,5 | 1, | | LO - 4 : | To be able to develop, select and use modern techniques and tools for digital signal processing applications by making effective use of information technologies. | 1,2,4,5 | 1, | | LO - 5 : | To be able to collect data for the examination of engineering problems in the field of digital signal processing and to analyze and interpret the results. | 1,2,4,5 | 1, | | CTPO : Contribution to programme outcomes, TOA :Type of assessment (1: written exam, 2: Oral exam, 3: Homework assignment, 4: Laboratory exercise/exam, 5: Seminar / presentation, 6: Term paper), LO : Learning Outcome | | |
| Discrete-time signals and systems, Discrete-time Fourier transform (DTFT), Discrete Fourier transform (DFT), Discrete-time processing of continuous-time signals, z-transform, Frequency domain analysis of linear and time-invariant systems, Digital filter design techniques |
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| Course Syllabus | | Week | Subject | Related Notes / Files | | Week 1 | Overview of signal and signal processing: Sign concept, Signal examples, Classification of signals, Analog and digital signal processing concepts, Advantages and shortcomings of digital signal processing, Matlab: Basic Concepts, Digital signal processing applications. | | | Week 2 | Overview of continuous-time signals and systems: Continuous-time signal models, Energy and power signals. | | | Week 3 | Overview of continuous-time signals and systems: Continuous-time systems and their properties, Frequency domain analysis of continuous-time signals and systems. | | | Week 4 | Overview of continuous-time signals and systems: Continuous-time systems and their properties, Frequency domain analysis of continuous-time signals and systems. | | | Week 5 | Digital processing of continuous-time signals: Sampling theory (ideal sampling, natural sampling and zero-order sampling), Sampling of band-pass signals. | | | Week 6 | Digital processing of continuous-time signals: Limitations of sampling in practice, signal reconstruction. | | | Week 7 | Digital processing of continuous-time signals: Quantization and Binary Coding. | | | Week 8 | Digital processing of continuous-time signals: ADC Implementations, Digital-to-analog conversion (DAC). | | | Week 9 | Midterm | | | Week 10 | Time domain definitions of discrete-time signals and systems: Discrete-time signal concept, basic operations in discrete-time signals, discrete-time signal models, discrete-time signal sizes. | | | Week 11 | Discrete-time signals and time domain descriptions of systems: Discrete-time systems and their examples, discrete-time LTI system descriptions, digital resampling | | | Week 12 | Analysis of discrete-time systems: Discrete-time systems defined by difference equations, z-transform | | | Week 13 | Analysis of discrete-time systems: z-transform, pole-zero representation and stability | | | Week 14 | Analysis of discrete-time systems: Inverse z-transform | | | Week 15 | Analysis of discrete-time systems: Realization of Digital Systems and Factors Affecting System Behavior | | | Week 16 | End-of-term exam | | | |
| 1 | A. H. Kayran, E. M. Ekşioğlu, 2010, Bilgisayar Uygulamalarıyla Sayısal İşaret İşleme, Birsen Yayınevi, 2. Basım, İstanbul. | | | |
| 1 | A. V. Oppenheim, R. W. Shafer, 1975., Digital Signal Processing, Prentice Hall, Englewood Cliffs. | | | |
| Method of Assessment | | Type of assessment | Week No | Date | Duration (hours) | Weight (%) | | Mid-term exam | 9 | | 2 | 50 | | End-of-term exam | 16 | | 2 | 50 | | |
| Student Work Load and its Distribution | | Type of work | Duration (hours pw) | No of weeks / Number of activity | Hours in total per term | | Yüz yüze eğitim | 3 | 14 | 42 | | Sınıf dışı çalışma | 1 | 16 | 16 | | Arasınav için hazırlık | 3 | 8 | 24 | | Arasınav | 2 | 1 | 2 | | Dönem sonu sınavı için hazırlık | 2 | 14 | 28 | | Dönem sonu sınavı | 2 | 1 | 2 | | Total work load | | | 114 |
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