Dimitri V. Nowicki

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Several architectures and algorithms of feed-forward networks and neural associative memories as well as GMDH-based polynomial NNs are tried for proteomic data analysis. The problem of chemotherapy responsiveness prediction by data of mass-spectroscopy is considered to explore potential applications of different neural paradigms for this domain.
This letter is devoted to the suppression of spurious signals (artifacts) in records of neural activity during deep brain stimulation. An approach based on nonlinear adaptive model with self-oscillations is proposed. We developed an algorithm of adaptive filtering based on this approach. The proposed algorithm was tested using recordings collected from(More)
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