Biyomedikal Mühendisliği

BME 427 | Ders Tanıtım Bilgileri

Dersin Adı

Adaptive Processing of Biomedical Signals

Kodu	Yarıyıl	Teori (saat/hafta)	Uygulama/Lab (saat/hafta)	Yerel Kredi	AKTS
BME 427	FALL	2	2	3	6

Ön-Koşul(lar)	Yok
Dersin Dili	English
Dersin Türü	ELECTIVE_COURSE
Dersin Düzeyi	Lisans
Dersin Veriliş Şekli	Face-To-Face
Dersin Öğretim Yöntem ve Teknikleri	Presentation Problem Solving Question/Answer
Ulusal Meslek Sınıflandırma Kodu	-
Dersin Koordinatörü	Prof. Dr. Aydın Akan
Öğretim Eleman(lar)ı	Prof. Dr. Aydın Akan
Yardımcı(ları)	Araş. Gör. Duygu Geçkin

Dersin Amacı

The aim of this course is to teach students the filtering methods required for adaptive analysis of biological signals. The modeling of random biological signals, their denoising, Wiener filter theory, and adaptive filter algorithms are covered.

Öğrenme Çıktıları

Bu dersi başarıyla tamamlayabilen öğrenciler;

Ad	Açıklama	PC Alt	* Katkı Düzeyi
Ad	Açıklama	PC Alt	1	2	3	4	5
LO1	will be able to explain the analysis and modeling of random signals.	1.5			X
LO2	will be able to explain adaptive learning algorithms	1.5			X
LO3	will be able to model adaptive filter theory and its application to biological signals.	4				X
LO4	will be able to design adaptive filters for noise cancellation problems encountered in Biomedical Engineering	3.2			X
LO5	will be able to define the concept of the Wiener filter	1.5		X

Ders Tanımı

This course covers the introduction and modeling of random processes where random biological signals are observed, stationary processes, linear optimum (Wiener) filtering, linear adaptive filtering, steepest descent, LMS and RLS learning algorithms, and Kalman filter theory.

Dersin İlişkili Olduğu Sürdürülebilir Kalkınma Amaçları

Dersin Kategorisi	Temel Ders
	Uzmanlık/Alan Dersleri	X
	Destek Dersleri
	İletişim ve Yönetim Becerileri Dersleri
	Aktarılabilir Beceri Dersleri

HAFTALIK KONULAR VE İLGİLİ ÖN HAZIRLIK ÇALIŞMALARI

Hafta	Konular	Ön Hazırlık	Öğrenme Çıktısı
1	Introduction to Random Signal Processing	"Haykin, S. S. (2002). Adaptive filter theory. Pearson Education India. CH 1.	LO1
2	Stationary random processes	"Haykin, S. S. (2002). Adaptive filter theory. Pearson Education India. CH 1.	LO1
3	Modeling of random processes	"Haykin, S. S. (2002). Adaptive filter theory. Pearson Education India. CH 1.	LO2
4	Autoregressive (AR) Model Estimation	"Haykin, S. S. (2002). Adaptive filter theory. Pearson Education India. CH 1.	LO3
5	Linear Prediction	"Haykin, S. S. (2002). Adaptive filter theory. Pearson Education India. CH 3.	LO2
6	Linear, least squares estimation	"Haykin, S. S. (2002). Adaptive filter theory. Pearson Education India. CH 2.	LO2
7	Linear adaptive filtering	"Haykin, S. S. (2002). Adaptive filter theory. Pearson Education India. CH 4.	LO3
8	Midterm		-
9	Gradient descent learning algorithm	"Haykin, S. S. (2002). Adaptive filter theory. Pearson Education India. CH 5.	LO3
10	Least Mean Squares (LMS) learning algorithm	"Haykin, S. S. (2002). Adaptive filter theory. Pearson Education India. CH 6.	LO3
11	Least squares (LS) adaptive filters	"Haykin, S. S. (2002). Adaptive filter theory. Pearson Education India. CH 9.	LO3
12	RLS learning algorithm	"Haykin, S. S. (2002). Adaptive filter theory. Pearson Education India. CH 10.	LO3
13	Adaptive noise cancellation solutions and Biomedical applications	"Haykin, S. S. (2002). Adaptive filter theory. Pearson Education India. CH 13.	LO4
14	Kalman and Wiener filter theory	Lecture notes	LO5
15	Review		-
16	Final Exam		-

Ders Kitabı	Haykin S. S. (2002). Adaptive filter theory. Pearson Education India. ISBN: 978-0132671453
Önerilen Okumalar/Materyaller	-

DEĞERLENDİRME ÖLÇÜTLERİ

Yarıyıl Aktiviteleri	Sayı	Katkı Payı %	LO1	LO2	LO3	LO4	LO5
Ödev	1	30	X	X	X	X	X
Ara Sınav	1	30	X	X	X
Final Sınavı	1	40	X	X	X	X	X
Toplam	3	100

AKTS / İŞ YÜKÜ TABLOSU

Yarıyıl Aktiviteleri	Sayı	Süre (Saat)	İş Yükü
Katılım	-	-	-
Teorik Ders Saati	16	2	32
Laboratuvar / Uygulama Ders Saati	16	2	32
Sınıf Dışı Ders Çalışması	14	2	28
Arazi Çalışması	-	-	-
Küçük Sınav / Stüdyo Kritiği	-	-	-
Portfolyo	-	-	-
Ödev	1	20	20
Sunum / Jüri Önünde Sunum	-	-	-
Proje	-	-	-
Seminer/Çalıştay	-	-	-
Sözlü Sınav	-	-	-
Ara Sınavlar	1	30	30
Final Sınavı	1	38	38
		Toplam	180

DERSİN ÖĞRENME ÇIKTILARININ PROGRAM YETERLİLİKLERİ İLE İLİŞKİSİ

#	PC Alt	Program Yeterlilikleri / Çıktıları	* Katkı Düzeyi
#	PC Alt	Program Yeterlilikleri / Çıktıları	1	2	3	4	5
1	Engineering Knowledge: Knowledge of mathematics, science, basic engineering, computation, and related engineering discipline-specific topics; the ability to apply this knowledge to solve complex engineering problems.
	1	Mathematics
	2	Science
	3	Basic Engineering
	4	Computation
	5	Related engineering discipline-specific topics		LO5	LO1 LO2
	6	The ability to apply this knowledge to solve complex engineering problems
2	Problem Analysis: Ability to identify, formulate and analyze complex engineering problems using basic knowledge of science, mathematics and engineering, and considering the UN Sustainable Development Goals relevant to the problem being addressed.
3	Engineering Design: The ability to devise creative solutions to complex engineering problems; the ability to design complex systems, processes, devices or products to meet current and future needs, considering realistic constraints and conditions.
	1	Ability to design creative solutions to complex engineering problems
	2	Ability to design complex systems, processes, devices or products to meet current and future needs, considering realistic constraints and conditions			LO4
4	Use of Techniques and Tools: Ability to select and use appropriate techniques, resources, and modern engineering and computing tools, including estimation and modeling, for the analysis and solution of complex engineering problems, while recognizing their limitations.					LO3
5	Research and Investigation: Ability to use research methods to investigate complex engineering problems, including literature research, designing and conducting experiments, collecting data, and analyzing and interpreting results.
	1	Literature research for the study of complex engineering problems
	2	Designing experiments
	3	Ability to use research methods, including conducting experiments, collecting data. analyzing and interpreting results
6	Global Impact of Engineering Practices: Knowledge of the impacts of engineering practices on society, health and safety, economy, sustainability, and the environment, within the context of the UN Sustainable Development Goals; awareness of the legal implications of engineering solutions.
	1	Knowledge of the impacts of engineering practices on society, health and safety, economy, sustainability, and the environment, within the context of the UN Sustainable Development Goals
	2	Awareness of the legal implications of engineering solutions
7	Ethical Behavior: Acting in accordance with the principles of the engineering profession, knowledge about ethical responsibility; awareness of being impartial, without discrimination, and being inclusive of diversity.
	1	Acting in accordance with the principles of the engineering profession, knowledge about ethical responsibility ethical responsibility
	2	Awareness of being impartial and inclusive of diversity, without discriminating on any subject
8	Individual and Teamwork: Ability to work effectively, individually and as a team member or leader on interdisciplinary and multidisciplinary teams (face-to-face, remote or hybrid).
	1	Ability to work individually and within the discipline
	2	Ability to work effectively as a team member or leader in multidisciplinary teams (face-to-face, remote or hybrid)
9	Verbal and Written Communication: Taking into account the various differences of the target audience (such as education, language, profession) on technical issues.
	1	Ability to communicate verbally
	2	Ability to communicate effectively in writing
10	Project Management: Knowledge of business practices such as project management and economic feasibility analysis; awareness of entrepreneurship and innovation.
	1	Knowledge of business practices such as project management and economic feasibility analysis
	2	Awareness of entrepreneurship and innovation
11	Lifelong Learning: Lifelong learning skills that include being able to learn independently and continuously, adapting to new and developing technologies, and thinking questioningly about technological changes.