EE 381K-6 Estimation Theory

Optimality of Kalman filter in linear dynamical systems with Gaussian inputs:

M. Welling, "The Kalman Filter," class notes.

Richard J. Meinhold and Singpurwalla N. D., "Understanding the Kalman-Filter," The American Statistician, May 1983, 37, 2, 123-127.

T. P. Minka, "From Hidden Markov Models to Linear Dynamical Systems," MIT Technical Report TR#531, 2000. (See Section 3).

Particle filtering tutorials:

P. Djuric et. al., "Particle Filtering",IEEE Signal Processing Magazine, vol. 20, no. 5, September 2003, pp: 19-38.

S. Arulampalam et. al., "A Tutorial on Particle Filters for On-line Non-linear/Non-Gaussian Bayesian Tracking," IEEE Transactions on Signal Processing, vol. 50, no.2, February 2002, pp. 174-188.

On Cramer-Rao lower bound:

D. Johnson, "Cramer-Rao Bound," brief tutorial on cnx.org, 2003.

Markov Chain Monte Carlo (MCMC):

B. Walsh, "Markov Chain Monte Carlo and Gibbs Sampling,"Lecture notes, 2004.

P. Djuric et. al., "Perfect Sampling: A Review and Applications to Signal Processing,"IEEE Transactions on Signal Processing, vol. 50, no. 2, February 2002, pp. 345-356.

Further links:
Sequential Monte Carlo Methods (at Cambridge University).