PAÜ .:. Eğitim Öğretim Bilgi Sistemi

COURSE INFORMATION

Course Code	Course Title	L+P Hour	Semester	ECTS
BMM 525	BIOMEDICAL SIGNAL PROCESSING	3 + 0	1st Semester	7,5

COURSE DESCRIPTION

Course Level	Doctorate Degree
Course Type	Elective
Course Objective	In this course, various estimation, detection and filtering methods are developed and demonstrated on biomedical signals. The methods include harmonic analysis, auto-regressive model, Wiener and Matched filters, linear discriminants and independent components. All methods will be developed on specific datasets such as ECG, EEG, MEG, Ultrasound. The lectures will be accompanied by data analysis assignments using MATLAB.
Course Content	Impulse response, Discrete Fourier transform and z-transform, Convolution, Sampling, Linear discriminants, Harmonic analysis, Auto-regressive model, Matched and Wiener filter, Independent components analysis.
Prerequisites	No the prerequisite of lesson.
Corequisite	No the corequisite of lesson.
Mode of Delivery	Face to Face

COURSE LEARNING OUTCOMES

1	Different estimations on biomedical signals
2	ECG, EEG, EMG, Ultrasound data sets will be developped.

COURSE'S CONTRIBUTION TO PROGRAM

Data not found.

ECTS ALLOCATED BASED ON STUDENT WORKLOAD BY THE COURSE DESCRIPTION

Activities	Quantity	Duration (Hour)	Total Work Load (Hour)
Course Duration (14 weeks/theoric+practical)	14	3	42
Mid-terms	1	56	56
Final examination	1	56	56
Special Study Module (Student)	1	41	41
Total Work Load ECTS Credit of the Course			195 7,5

COURSE DETAILS

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L+P: Lecture and Practice
PQ: Program Learning Outcomes
LO: Course Learning Outcomes

Prospective Student