Abstract
We present a nonlinear inverse filtering approach to problems such as power spectrum estimation of stationary time series or deconvolution of a blurred image. The technique is based on eigenvalue optimization and a numerical treatment may therefore be obtained using primal-dual interior-point methods for semidefinite programming.
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