Estimate the signal from its noisy observation using a linear filter designed by minimizing the mean square error (Wiener Filter)

1. Lathi, B.P. and Ding, Z., 1998. Modern digital and analog communication systems (Vol. 3, pp. 184-187). New York: Oxford University Press.

  1. Kay, S. M., 1988. Modern Spectral Estimation: Theory and Application. Englewood Cliffs, NJ, USA: Prentice Hall.

  2. Kay, S. M., 1993. Fundamentals of Statistical Signal Processing, Volume I: Estimation Theory. Upper Saddle River, NJ, USA: Prentice Hall.

  3. Papoulis, A. and Pillai, S. U., 2002. Probability, Random Variables, and Stochastic Processes, 4th ed. New York, NY, USA: McGraw-Hill.

  4. Gray, R. M. and Davisson, L. D., 2004. Introduction to Statistical Signal Processing. Cambridge, U.K.: Cambridge University Press.

  5. Stoica, P. and Moses, R., 2005. Spectral Analysis of Signals. Upper Saddle River, NJ, USA: Pearson Prentice Hall.

  6. Proakis, J. G. and Manolakis, D. G., 2007. Digital Signal Processing: Principles, Algorithms, and Applications, 4th ed. Upper Saddle River, NJ, USA: Pearson Prentice Hall.

  7. Haykin, S., 2008. Communication Systems. Hoboken, NJ, USA: John Wiley & Sons.

  8. Proakis, J. G. and Salehi, M., 2008. Digital Communications. New York, NY, USA: McGraw-Hill.

  9. Haykin, S., 2013. Adaptive Filter Theory, 5th ed. Upper Saddle River, NJ, USA: Pearson.

  10. Box, G. E. P., Jenkins, G. M., Reinsel, G. C., and Ljung, G. M., 2015. Time Series Analysis: Forecasting and Control, 5th ed. Hoboken, NJ, USA: John Wiley & Sons.

  11. Oppenheim, A. V. and Verghese, G. C., 2017. Signals, Systems & Inference. London, UK: Pearson.