Montillet, Jean-Philippe; McClusky, Simon; Yu, Kegen
In the analysis of some specific time series (e.g., Global Positioning System coordinate time series, chaotic time series, human brain imaging), the noise is generally modeled as a sum of a power-law noise and white noise. Some existing softwares estimate the amplitude of the noise components using convex optimization (e.g., Levenberg-Marquadt) applied to a log-likelihood cost function. This work studies a novel cost function based on an approximation of the negentropy. Restricting the study to...[Show more]
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