Increasing the accuracy of signal extraction by correcting the approximating function under conditions of a priori uncertainty
The paper discusses the issues of practical implementation of increasing the accuracy of signal extraction, which is achieved by eliminating the «flip» of the approximating function when dividing the measured process into intervals under conditions of a priori uncertainty about the signal function,...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
EDP Sciences
2021-01-01
|
| Series: | E3S Web of Conferences |
| Online Access: | https://www.e3s-conferences.org/articles/e3sconf/pdf/2021/55/e3sconf_eeests2021_02003.pdf |
| _version_ | 1818665847155064832 |
|---|---|
| author | Nikishin Ivan Marchuk Vladimir Shrayfel Igor Sadrtdinov Ilya |
| author_facet | Nikishin Ivan Marchuk Vladimir Shrayfel Igor Sadrtdinov Ilya |
| author_sort | Nikishin Ivan |
| collection | DOAJ |
| description | The paper discusses the issues of practical implementation of increasing the accuracy of signal extraction, which is achieved by eliminating the «flip» of the approximating function when dividing the measured process into intervals under conditions of a priori uncertainty about the signal function, which significantly increases the error of allocating a useful signal. The probability of a «flip» of the approximating function depends significantly on the variance of the additive noise and the sample length. The use of the proposed methods and their software implementation makes it possible to increase the accuracy of the useful signal extraction up to 30 percent in the absence of a priori information about the function of the measured process for complex signals and at least 20% for simpler ones. The use of the proposed methods will significantly increase the processing efficiency in the conditions of a priori uncertainty about the function of the measured process (useful signal) and the statistical characteristics of the additive noise components. |
| first_indexed | 2024-12-17T05:55:08Z |
| format | Article |
| id | doaj.art-a3a191a0e22f415085627d2c3185f8b9 |
| institution | Directory Open Access Journal |
| issn | 2267-1242 |
| language | English |
| last_indexed | 2024-12-17T05:55:08Z |
| publishDate | 2021-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | E3S Web of Conferences |
| spelling | doaj.art-a3a191a0e22f415085627d2c3185f8b92022-12-21T22:01:03ZengEDP SciencesE3S Web of Conferences2267-12422021-01-012790200310.1051/e3sconf/202127902003e3sconf_eeests2021_02003Increasing the accuracy of signal extraction by correcting the approximating function under conditions of a priori uncertaintyNikishin IvanMarchuk VladimirShrayfel IgorSadrtdinov IlyaThe paper discusses the issues of practical implementation of increasing the accuracy of signal extraction, which is achieved by eliminating the «flip» of the approximating function when dividing the measured process into intervals under conditions of a priori uncertainty about the signal function, which significantly increases the error of allocating a useful signal. The probability of a «flip» of the approximating function depends significantly on the variance of the additive noise and the sample length. The use of the proposed methods and their software implementation makes it possible to increase the accuracy of the useful signal extraction up to 30 percent in the absence of a priori information about the function of the measured process for complex signals and at least 20% for simpler ones. The use of the proposed methods will significantly increase the processing efficiency in the conditions of a priori uncertainty about the function of the measured process (useful signal) and the statistical characteristics of the additive noise components.https://www.e3s-conferences.org/articles/e3sconf/pdf/2021/55/e3sconf_eeests2021_02003.pdf |
| spellingShingle | Nikishin Ivan Marchuk Vladimir Shrayfel Igor Sadrtdinov Ilya Increasing the accuracy of signal extraction by correcting the approximating function under conditions of a priori uncertainty E3S Web of Conferences |
| title | Increasing the accuracy of signal extraction by correcting the approximating function under conditions of a priori uncertainty |
| title_full | Increasing the accuracy of signal extraction by correcting the approximating function under conditions of a priori uncertainty |
| title_fullStr | Increasing the accuracy of signal extraction by correcting the approximating function under conditions of a priori uncertainty |
| title_full_unstemmed | Increasing the accuracy of signal extraction by correcting the approximating function under conditions of a priori uncertainty |
| title_short | Increasing the accuracy of signal extraction by correcting the approximating function under conditions of a priori uncertainty |
| title_sort | increasing the accuracy of signal extraction by correcting the approximating function under conditions of a priori uncertainty |
| url | https://www.e3s-conferences.org/articles/e3sconf/pdf/2021/55/e3sconf_eeests2021_02003.pdf |
| work_keys_str_mv | AT nikishinivan increasingtheaccuracyofsignalextractionbycorrectingtheapproximatingfunctionunderconditionsofaprioriuncertainty AT marchukvladimir increasingtheaccuracyofsignalextractionbycorrectingtheapproximatingfunctionunderconditionsofaprioriuncertainty AT shrayfeligor increasingtheaccuracyofsignalextractionbycorrectingtheapproximatingfunctionunderconditionsofaprioriuncertainty AT sadrtdinovilya increasingtheaccuracyofsignalextractionbycorrectingtheapproximatingfunctionunderconditionsofaprioriuncertainty |