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)
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.