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Next: Match Filtering for Attenuation Up: Homework 4 Previous: Prerequisites

Theoretical part

You can either write your answers to theoretical questions on paper or edit them in the file hw4/paper.tex. Please show all the mathematical derivations that you perform.

  1. The following equality for the posterior model covariance was given in lecture notes without a proof:
    \begin{displaymath}
\widehat{\mathbf{C}_m} = \left(\mathbf{F}^T\,\mathbf{C}_n^...
...f{F}^T + \mathbf{C}_n\right)^{-1}\,\mathbf{F}\,\mathbf{C}_m\;.
\end{displaymath} (1)

    Prove it.

  2. If the model shaping operator $\mathbf{S}_m$ admits a symmetric splitting $\mathbf{S}_m=\mathbf{H}_m \mathbf{H}_m^T$ with square and invertible $\mathbf{H}_m$, the model shaping equation can be rewritten in a symmetric form
    \begin{displaymath}
\left[\mathbf{I} + \mathbf{S}_m (\mathbf{B F - I})\right]^...
...}) \mathbf{H}_m\right]^{-1} \mathbf{H}_m^T \mathbf{B d}\;.
\end{displaymath} (2)

    1. Prove equation (2).
    2. Assuming a symmetric splitting for the data shaping operator $\mathbf{S}_d=\mathbf{H}_d^T \mathbf{H}_d$, find a symmetric form of the data shaping equation
      \begin{displaymath}
\mathbf{B} \left[\mathbf{I} + \mathbf{S}_d (\mathbf{F B - I})\right]^{-1}  \mathbf{S}_d \mathbf{d} = \hfill \
\end{displaymath} (3)


next up previous [pdf]

Next: Match Filtering for Attenuation Up: Homework 4 Previous: Prerequisites

2022-10-19