Course Information

Course Name	Turkish	İzge Kestirim Yöntemleri
	English	Spectral Estimation Methods
Course Code	TEL 608E	Credit	Lecture (hour/week)	Recitation (hour/week)	Laboratory (hour/week)
Semester	-	3	-	-	-
Course Language		English
Course Coordinator		Tayfun Akgül
Course Objectives		1. This course will introduce the fundamentals of the classic and modern spectral estimation techniques. 2. Techniques for comprehensive analysis and synthesis methods will be explained. 3. Advantages and disadvantages of estimation methods will be discussed. 4. For various signals, applications of the parametric and non parametric spectral estimation methods will be covered.
Course Description		An overview of concepts of spectral analysis covering traditional approaches and modern estimation methods will include: Probability density functions; expectations; processes; correlation and covariance, matrix and vector manipulations; discrete-time random signals; energy and power spectral densities. Nonparametric Spectral Estimations: Periodogram; averaged periodogram, Blackman-Tukey method, other refined periodogram methods (Bartlett, Welch, Daniell methods); Statistical properties of nonparametric spectral estimators; Rational spectral models -Autoregressive spectral estimation; Moving average spectral estimation; Autoregressive moving average spectral estimation; Yule-Walker equations; parameter estimation techniques; statistical properties. Filter-bank based approaches: Filter-bank interpretation of the periodogram, Capon method, relationship between Capon and AR methods. Advanced Concepts: Sinusiodal parameter estimation, MUSIC, ESPRIT. Introduction to Array Signal Processing: Problem statement; relationship to line spectral estimation. Array Signal Processing: Nonparametric and parametric estimation techniques; properties. Applications: Topics related to underwater acoustic, sonar, radar signal analyses and biosignal analysis.
Course Outcomes		M.Sc./Ph.D. students who successfully pass this course gain knowledge, skill and competency in the following subjects; 1. Fundamentals of the classical and modern spectral estimation methods. 2. Various techniques for comprehensive analysis and synthesis methods will be studied. 3. Parametric and nonparametric modeling techniques for spectral analysis will be covered. 4. Applications (using real signals) of the parametric and non parametric spectral estimation techniques.
Pre-requisite(s)
Required Facilities
Other
Textbook		Steven M. Kay, Modern Spectrum Estimation: Theory and Application, Prentice-Hall, 1988.
Other References		2. P. Stoica, R.L. Moses, Introduction to Spectral Analysis, Prentice-Hall, 1997. 3. P. Stoica, R.L. Moses, Spectral Analysis of Signals, Prentice-Hall, 2005. 4. D.G. Manolakis, D. Manolakis,V.K. Ingle, S. M. Kogon, Statistical and Adaptive Signal Processing: Spectral Estimation, Signal Modelling, Adaptive Filtering and Array Processing, Artech House Signal Processing Library, 2005.

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