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- W3033795991 abstract "The article discusses the detection and identification of seismic P wave using a recurrent neural network. The results of the neural network depend on the preparation of the source data. In this research we compared the results of a recurrent neural network with raw data, filtered data and filtered data with added attributes fourth-order autoregressive coefficients. In our experiments on the seismic data we have reached 89,71 % accuracy that have shown this technique to be promising for classification and detection of P wave arrival moment." @default.
- W3033795991 created "2020-06-12" @default.
- W3033795991 creator A5053832446 @default.
- W3033795991 date "2020-02-13" @default.
- W3033795991 modified "2023-09-23" @default.
- W3033795991 title "PRELIMINARY DATA PROCESSING FOR LEARNING A NEURAL NETWORK IN THE PROBLEM OF DETECTION AND IDENTIFICATION OF SIGNALS ON THE BACKGROUND OF COLOR NOISES" @default.
- W3033795991 cites W2069692647 @default.
- W3033795991 doi "https://doi.org/10.31618/2658-7556-2020-41-2-3" @default.
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