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Information
| Code | EE684 |
| Name | Adaptive Filter Theory |
| Semester | . Semester |
| Duration (T+A) | 3-0 (T-A) (17 Week) |
| ECTS | 6 ECTS |
| National Credit | 3 National Credit |
| Teaching Language | İngilizce |
| Level | Doktora Dersi |
| Type | Normal |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator | Prof. Dr. SAMİ ARICA |
Course Goal
The course provides filtering of stationary and nonstationary signals. The course presents digital systems which tune in automatically and adapt to the environment. The student is given enough theoretical and practical knowledge to independently be able to formulate the mathematical problem, solve it and implement the solution for use with real-life signals.
Course Content
Random process. Moving average (MA), Autoregressive (AR) and ARMA models. Wiener filtering. Linear prediction. Levinson-Durbin algorithm. Lattice filters. Steepest Descent method. Least mean squares (LMS) method and its variants. Finite and infinite response LMS filters. Recursive least squares (RLS). Kalman filters.
Course Precondition
There are no prerequisites for the course.
Resources
Adaptive Filter Theory by Simon O. Haykin
Notes
No suggested additional course notes.
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | To have knowledge about and understand the main concepts in optimum and adaptive filter theory. |
| LO02 | To be able to apply the most commonly used methods to real problems and real-life signals. |
| LO03 | To be able to formulate mathematical problems based on described situations. |
| LO04 | Capable of applying the concepts gained in the course for Adaptive Signal Processing to his or her thesis and applications in the real world. |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | Bilgi - Kuramsal, Olgusal | Being able to specialize in at least one of the branches that form the foundations of Electrical and Electronics Engineering by increasing the level of knowledge beyond the master's level | 4 |
| PLO02 | Bilgi - Kuramsal, Olgusal | To comprehend the integrity of all the subjects included in the field of specialization. | 3 |
| PLO03 | Bilgi - Kuramsal, Olgusal | Having knowledge of the current scientific literature in the field of specialization to analyze the literature critically | 3 |
| PLO04 | Bilgi - Kuramsal, Olgusal | To comprehend the interdisciplinary interaction of the field with other related branches, to suggest similar interactions. | 3 |
| PLO05 | Bilgi - Kuramsal, Olgusal | Ability to do theoretical and experimental work | 3 |
| PLO06 | Bilgi - Kuramsal, Olgusal | To create a complete scientific text by compiling the information obtained from the research | |
| PLO07 | Bilgi - Kuramsal, Olgusal | To work on the thesis topic programmatically, following the logical integrity required by the subject within the framework determined by the advisor. | |
| PLO08 | Bilgi - Kuramsal, Olgusal | To search for literature in scientific databases, particularly the ability to correctly and accurately scan databases and evaluate and categorize listed items. | 3 |
| PLO09 | Bilgi - Kuramsal, Olgusal | Having a command of English and related English jargon at a level that can easily read and understand a scientific text written in English in the field of specialization and write a similar text | |
| PLO10 | Bilgi - Kuramsal, Olgusal | Ability to write a computer program in a familiar programming language, generally for a specific purpose, specifically related to the field of expertise. | |
| PLO11 | Bilgi - Kuramsal, Olgusal | Ability to plan and teach lessons related to the field of specialization or related fields | |
| PLO12 | Bilgi - Kuramsal, Olgusal | Being able to guide and take the initiative in environments that require solving problems related to the field | |
| PLO13 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Ability to communicate with people in an appropriate language | |
| PLO14 | Yetkinlikler - Öğrenme Yetkinliği | Adopting the ethical values required by both education and research aspects of academician | |
| PLO15 | Yetkinlikler - Öğrenme Yetkinliği | To be able to produce projects, policies, and processes in the field of expertise and to evaluate these elements | |
| PLO16 | Yetkinlikler - Öğrenme Yetkinliği | Ability to research new topics based on existing research experience |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | Introduction. Linear filtering problem. Adaptive filters. Application of adaptive filters. Stationary discrete-time stochastic processes. | Textbook reading/Problem solving/Computer application. | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
| 2 | Stationary discrete-time stochastic processes (cont.). Moving average (MA), Autoregressive (AR) and ARMA models. | Textbook reading/Problem solving/Computer application. | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
| 3 | Moving average (MA), Autoregressive (AR) and ARMA models (cont.). | Textbook reading/Problem solving/Computer application. | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
| 4 | Wiener filter theory. | Textbook reading/Problem solving/Computer application. | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
| 5 | Linear prediction. | Textbook reading/Problem solving/Computer application. | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
| 6 | Linear prediction (cont.). | Textbook reading/Problem solving/Computer application. | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
| 7 | Steepest Descent method. Least mean squares (LMS) method and its variants. | Textbook reading/Problem solving/Computer application. | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
| 8 | Mid-Term Exam | Textbook reading/Problem solving. | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
| 9 | Kalman filter. | Textbook reading/Problem solving/Computer application. | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
| 10 | Kalman filter (cont.). | Textbook reading/Problem solving/Computer application. | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
| 11 | Method of least squares. | Textbook reading/Problem solving/Computer application. | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
| 12 | Recursive least squares (RLS) filters. | Textbook reading/Problem solving/Computer application. | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
| 13 | Recursive least squares (RLS) filters (cont.). | Textbook reading/Problem solving/Computer application. | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
| 14 | Lattice filters. | Textbook reading/Problem solving/Computer application. | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
| 15 | Lattice filters (cont.). | Textbook reading/Problem solving/Computer application. | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
| 16 | Term Exams | Textbook reading/Problem solving. | Ölçme Yöntemleri: Yazılı Sınav |
| 17 | Term Exams | Textbook reading/Problem solving. | Ölçme Yöntemleri: Yazılı Sınav |
Student Workload - ECTS
| Works | Number | Time (Hour) | Workload (Hour) |
|---|---|---|---|
| Course Related Works | |||
| Class Time (Exam weeks are excluded) | 14 | 3 | 42 |
| Out of Class Study (Preliminary Work, Practice) | 14 | 6 | 84 |
| Assesment Related Works | |||
| Homeworks, Projects, Others | 7 | 4 | 28 |
| Mid-term Exams (Written, Oral, etc.) | 1 | 2 | 2 |
| Final Exam | 1 | 2 | 2 |
| Total Workload (Hour) | 158 | ||
| Total Workload / 25 (h) | 6,32 | ||
| ECTS | 6 ECTS | ||