Signaling in neuronal networks plays a crucial role in regulating the processes of proper network formation during development and learning in the matured nervous system. Adaptation of neuronal networks to the culture...
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In the current paper we provide a proof of NP-completeness for the Cell Formation Problem (CFP) with the fractional grouping efficacy objective. For this purpose we first consider the CFP with the linear objective min...
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We prove the existence of a continuous Morse energy function for an arbitrary topological flow with finite hyperbolic (in topological sense) chain recurrent set on a topological manifold of any dimension. This result ...
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作者：
Kruglov, Vladislav E.Malyshev, Dmitry S.Pochinka, Olga V.HSE Campus in Nizhny Novgorod
Faculty of Informatics Mathematics and Computer Science Laboratory of Topological Methods in Dynamics. Trainee Researcher Lobachevsky State University of Nizhny Novgorod Institute ITMM Department of Mathematical Physics Optimal Control Master’s HSE Campus in Nizhny Novgorod
Laboratory of Algorithms and Technologies for Networks Analysis. Leading Research Fellow HSE Campus in Nizhny Novgorod Faculty of Informatics Mathematics and Computer Science Department of Applied Mathematics and Informatics Lobachevsky State University of Nizhny Novgorod Institute ITMM Department of Algebra Geometry and Discrete Mathematics HSE Campus in Nizhny Novgorod
Faculty of Informatics Mathematics and Computer Science Department of Fundamental Mathematics Department Head. HSE Campus in Nizhny Novgorod Faculty of Informatics Mathematics and Computer Science Laboratory for Topological Methods in Dynamics. Laboratory
Structurally stable (rough) flows on surfaces have only finitely many singularities and finitely many closed orbits, all of which are hyperbolic, and they have no trajectories joining saddle points. The violation of t...
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This paper is devoted to methods of processing hydrophone records in order to identify specific signals, produced by marine mammals. The aim of processing is to detect a signal according to a certain pattern against t...
This paper is devoted to methods of processing hydrophone records in order to identify specific signals, produced by marine mammals. The aim of processing is to detect a signal according to a certain pattern against the background of non-stationary noise. Development of a robust detection algorithm is of great interest because it could help to assess marine mammal occurrence and distribution at greater temporal and spatial scales by excluding laborious task of manually analyzing acoustic data. In addition, such algorithm may be implemented in automatic systems designed to warn vessel crew to avoid potential collision with whales. The data, studied in this paper, contained the calls of North Atlantic right whales, that were collected in the Gulf of St. Lawrence. Machine learning is exploited to solve a signal detection problem. The model was trained by a set of manually labelled signal fragments. Each fragment is labelled whether a whale call is present or not in the fragment. The proposed detection method is based on the two-level stacked gradient boosting models (XGBoost algorithm). The first-level model deals with spectral features, extracted from the short signal frames. The second model accumulates estimated output for a group of subsequent frames.
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