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Signal Processing

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  • $\begingroup$ I am trying to understand if I can articulate your answer in CVX (does adding weight render the problem to be non-convex?)... First, if I understand correctly the norm to be minimized $C^{-1}$ is the inverse(?) of the covariance matrix given by $C= (y−Ax)^T diag(c) (y−Ax)$ ?and to obtain the inverse I can use Cholesky Decomposition or etc? $\endgroup$ Commented Nov 11, 2021 at 20:36
  • $\begingroup$ @bla Adding the weighting does not make the problem non-convex. $\endgroup$ Commented Nov 11, 2021 at 22:39
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    $\begingroup$ @bla, Since $ {C}^{-1} = \operatorname{diag} \left( \boldsymbol{c}^{-1} \right) $ you can easily define $ {C}^{-1} $ and use quad_form() from CVX. You may mark this as answered and open a question specifically how to solve my form in CVX and I will post code. $\endgroup$ Commented Nov 12, 2021 at 5:48
  • $\begingroup$ dsp.stackexchange.com/questions/79087/… $\endgroup$ Commented Nov 12, 2021 at 8:54