Lehrinhalte
Signal detection and parameter estimation are fundamental signal processing tasks. In fact, they appear in many common engineering operations under a variety of names. In this course, the theory behind detection and estimation will be presented, allowing a better understanding of how (and why) to design "good" detection and estimation schemes.
These lectures will cover: Fundamentals
Detection Theory Hypothesis Testing Bayesian Tests
Ideal Observer Tests
Neyman-Pearson Tests
Receiver Operating Characteristics
Uniformly Most Powerful Tests
The Matched Filter Estimation Theory Types of Estimators
Maxmimum Likelihood Estimators
Sufficiency and the Fisher-Neyman/Factorisation Criterion
Unbiasedness and Minimum variance
Fisher Information and the CRB
Asymptotic properties of the MLE
Literatur
[list]
[*]Lecture slides
[*]Jerry D. Gibson and James L. Melsa. Introduction to Nonparametric Detection with Applications. IEEE Press, 1996.
[*]S. Kassam. Signal Detection in Non-Gaussian Noise. Springer Verlag, 1988.
[*]S. Kay. Fundamentals of Statistical Signal Processing: Estimation Theory. Prentice Hall,
1993.
[*]S. Kay. Fundamentals of Statistical Signal Processing: Detection Theory. Prentice Hall, 1998.
[*]E. L. Lehmann. Testing Statistical Hypotheses. Springer Verlag, 2nd edition, 1997.
[*]E. L. Lehmann and George Casella. Theory of Point Estimation. Springer Verlag, 2nd edition, 1999.
[*]Leon-Garcia. Probability and Random Processes for Electrical Engineering. Addison Wesley, 2nd edition, 1994.
[*]P. Peebles. Probability, Random Variables, and Random Signal Principles. McGraw-Hill, 3rd edition, 1993.
[*]H. Vincent Poor. An Introduction to Signal Detection and Estimation. Springer Verlag, 2nd edition,
1994.
[*]Louis L. Scharf. Statistical Signal Processing: Detection, Estimation, and Time Series Analysis. Pearson Education POD, 2002.
[*]Harry L. Van Trees. Detection, Estimation, and Modulation Theory, volume I,II,III,IV. John Wiley & Sons, 2003.
[*]A. M. Zoubir and D. R. Iskander. Bootstrap Techniques for Signal Processing. Cambridge University Press, May 2004.
[/list]
Voraussetzungen
DSP, general interest in signal processing
Signal detection and parameter estimation are fundamental signal processing tasks. In fact, they appear in many common engineering operations under a variety of names. In this course, the theory behind detection and estimation will be presented, allowing a better understanding of how (and why) to design "good" detection and estimation schemes.
These lectures will cover: Fundamentals
Detection Theory Hypothesis Testing Bayesian Tests
Ideal Observer Tests
Neyman-Pearson Tests
Receiver Operating Characteristics
Uniformly Most Powerful Tests
The Matched Filter Estimation Theory Types of Estimators
Maxmimum Likelihood Estimators
Sufficiency and the Fisher-Neyman/Factorisation Criterion
Unbiasedness and Minimum variance
Fisher Information and the CRB
Asymptotic properties of the MLE
Literatur
[list]
[*]Lecture slides
[*]Jerry D. Gibson and James L. Melsa. Introduction to Nonparametric Detection with Applications. IEEE Press, 1996.
[*]S. Kassam. Signal Detection in Non-Gaussian Noise. Springer Verlag, 1988.
[*]S. Kay. Fundamentals of Statistical Signal Processing: Estimation Theory. Prentice Hall,
1993.
[*]S. Kay. Fundamentals of Statistical Signal Processing: Detection Theory. Prentice Hall, 1998.
[*]E. L. Lehmann. Testing Statistical Hypotheses. Springer Verlag, 2nd edition, 1997.
[*]E. L. Lehmann and George Casella. Theory of Point Estimation. Springer Verlag, 2nd edition, 1999.
[*]Leon-Garcia. Probability and Random Processes for Electrical Engineering. Addison Wesley, 2nd edition, 1994.
[*]P. Peebles. Probability, Random Variables, and Random Signal Principles. McGraw-Hill, 3rd edition, 1993.
[*]H. Vincent Poor. An Introduction to Signal Detection and Estimation. Springer Verlag, 2nd edition,
1994.
[*]Louis L. Scharf. Statistical Signal Processing: Detection, Estimation, and Time Series Analysis. Pearson Education POD, 2002.
[*]Harry L. Van Trees. Detection, Estimation, and Modulation Theory, volume I,II,III,IV. John Wiley & Sons, 2003.
[*]A. M. Zoubir and D. R. Iskander. Bootstrap Techniques for Signal Processing. Cambridge University Press, May 2004.
[/list]
Voraussetzungen
DSP, general interest in signal processing
- Lehrende: Abdelhak Zoubir
Semester: Verão 2019