Abstract
An algorithm for noise suppression and extraction of coherent structures of a complex signal is proposed. The algorithm is based on the joint application of packet wavelet decompositions and adaptive stochastic thresholds. Thresholds are estimated with a given confidence level based on the α-quantiles of Student's distribution. The operations of the algorithm are described and a scheme for its implementation is proposed. On the example of data from neutron monitors (recording the intensity of secondary cosmic rays, www.nmdb.eu), the efficiency of the algorithm is shown. The selected coherent structures characterize the occurrence of anomalies in variations in the intensity of cosmic rays. Anomalies in cosmic ray data create a radiation hazard, disrupt radio communications, and cause satellites to malfunction, leading to disorientation and destruction. Therefore, the task of timely diagnosis of such events is relevant. The application of the algorithm made it possible to clearly detect and evaluate the moments of occurrence of anomalies in cosmic rays, which were observed during periods of magnetospheric disturbances.
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