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  • 12:08 PM, Sunday, 17 Nov 2019


Course Undergraduate
Semester Electives
Subject Code AV466
Subject Title Estimation and Stochastic Theory

Syllabus

Elements of probability theory  ‐ random variables‐Gaussian distribution‐stochastic processes‐ characterizations and properties‐Gauss‐Markov processes‐Brownian motion process‐Gauss‐ Markov models  ‐  Optimal estimation for discrete‐time systems  ‐  fundamental theorem of estimation‐optimal prediction.

Optimal filtering  ‐  Weiner approach‐continuous time Kalman Filter‐properties and implementation‐steady‐state Kalman Filter‐discrete‐time Kalman Filter‐implementation‐sub‐ optimal steady‐state Kalman Filter‐Extended Kalman Filter‐practical applications

Optimal smoothing  ‐  0ptimal fixed‐interval smoothing optimal fixed‐point smoothing‐optimal fixed‐lag smoothing‐stability‐performance evaluation.

Elements of probability theory ‐ random variables‐Gaussian distribution‐stochastic processescharacterizations and properties‐Gauss‐Markov processes‐Brownian motion process‐Gauss‐ Markov models ‐ Optimal estimation for discrete‐time systems ‐ fundamental theorem of estimation‐optimal prediction. Optimal filtering ‐ Weiner approach‐continuous time Kalman Filter‐properties and implementation‐steady‐state Kalman Filter‐discrete‐time Kalman Filter‐implementation‐suboptimal steady‐state Kalman Filter‐Extended Kalman Filter‐practical applications. Optimal smoothing ‐ 0ptimal fixed‐interval smoothing optimal fixed‐point smoothing‐optimal fixed‐lag smoothing‐stability‐performance evaluation.

Text Books

1. M.D. Srinath, P.K. Rajasekaran and R. Viswanathan: Statistical Signal Processing with Applications, PHI, 1996.

2. D.G. Manolakis, V.K. Ingle and S.M. Kogon: Statistical and Adaptive Signal Processing, McGraw Hill, 2000.

3. S. M. Kay: Modern Spectral Estimation, Prentice Hall, 1987.

4. H. V. Poor, "An Introduction to Signal Detection and Estimation", Springer, 2/e, 1998.

5. S. M. Kay, "Fundamentals of Statistical Signal Processing: Estimation Theory", Prentice Hall PTR, 1993.

6. M.S. Grewal, A.P. Andrews, “Kalman filtering : Theory and Practice”, Second edition, John Wiley & Sons, 2001.

7. C.K. Chui, G. Chen, “Kalman Filtering with Real‐Time Applications”, Third edition, Springer‐Verlag,1999.

8. R.G. Brown, Y.C. Hwang, “Introduction to Random Signals and Applied Kalman Filtering”, Second edition, John Wiley & Sons, 1992

References

Same as Textbooks