Statistical Signal Processing AA 2006/07

Statistical Signal Processing AA 2006/07


Introduction: examples of statistical reasoning (2h) [1].


Rudiments of Multivariate Normal Theory (10h) [1, 6].


Estimation Theory: Sufficiency and MVUB Estimators. Maximum
Likelihood Estimators and Cramer
-
Rao bo
und; Bayes estimators:
minimum mean
-
squared error (MMSE); linear MMSE estimators;
Wiener filtering (20 h) [1, 2, 3, 4, 6].


Detection Theory: Neyman
-
Pearson Lemma, Testing of composite binary
hypotheses, UMP tests, Constant False Alarm Rate property; Baye
s
detectors (15h) [1, 2, 3, 4, 6].


Applications to radar signal processing (10h) [2, 6].


Applications to communication theory (15h) [5, 6].



References


[1] L. L. Scharf, ``Statistical Signal Processing: Detection, Estimation,
and Time Series Analysis,
’’ Addison
-
Wesley, 1991.

[2] H. L. Van trees, ``Detection, Estimation and Modulation Theory,’’
Part. 1 e 4, John Wiley & Sons.

[3] S. M. Kay: ``Fundamentals of Statistical Signal Processing, Volume I:
Estimation Theory,’’ Prentice
-
Hall, 1993.

[4] S. M. Kay
: ``Fundamentals of Statistical Signal Processing, Volume I:
Detection Theory,’’ Prentice
-
Hall, 1998.

[5] U. Mengali, A. N. D’Andrea: ``Synchronization Techniques for
Digital Receivers,’’ Plenum Press, 1997.

[6] Handouts (in progress).