We mainly use lecture notes and some papers, which can be downloaded from
- J.M. Mendel, Lessons in Estimation Theory for Signal Processing, Communications and
Control, Prentice Hall, Englewood Cliffs, New Jersey, 1995.
- A. Bjorck, Numerical Methods in Matrix Computations (Chapter 2, Section 4.5), Springer, 2015.
- T. Hastie, J.H. Friedman, and R. Tibshirani. The Elements of Statistical Learning: Data Mining, Inference, and Prediction. Springer, 2nd
- T. Kailath, A.H. Sayed, and B. Hassibi, Linear Estimation, Prentice Hall,
Upper Saddle River, NJ, 2000.
- P.C. Hansen, V. Pereyra, G. Scherer,
Least Squares Data Fitting with Applications,
The Johns Hopkins University Press, 2013.