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In the sparse representation field recent studies using composite dictionaries have shown encouraging results in performing noise removal. In this paper we look at dictionary composition in the particular case of dictionaries structured as a union of orthonormal bases. Our study focuses on denoising performance, providing new algorithms that outperform existing solutions, and also speed, resulting...
This paper proposes a set-based parameter identification method for biochemical systems. The developed method identifies not a single parameter but a set of parameters that all explain time-series experimental data, enabling the systematic characterization of the uncertainty of identified parameters. Our key idea is to use a state-space realization that has the same input-output behavior as experimental...
We investigate the problem of estimating a constant based on noisy observations via a binary sensor. This problem is well-studied for the case when the noise characteristics are known, for example, the noise is i.i.d. and we have access to its cumulative distribution function (CDF). Here, we try to reduce the assumptions on the noise to a minimum and, for example, assume only that the noise is symmetrically...
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