Применение итерационного алгоритма вейвлет-преобразования для обнаружения узкополосных сигналов; Вестник компьютерных и информационных технологий; № 8 (122)
| Parent link: | Вестник компьютерных и информационных технологий: научно-технический и производственный журнал.— , 2004- № 8 (122).— 2014.— [С. 17-22] |
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| Glavni avtor: | |
| Korporativna značnica: | |
| Izvleček: | Заглавие с экрана Рассмотрено применение итерационного алгоритма непрерывного вейвлет-преобразования для обнаружения узкополосных сигналов на фоне широкополосного шума. Предложено дополнение алгоритма критерием обнаружения узкополосных сигналов по локальным максимумам распределения дисперсии вейвлет-коэффициентов. Представлены результаты применения алгоритма на тестовых сигналах с отрицательным значением отношения сигнал/шум. The application of the iterative algorithm for continuous wavelet transform for the detection of narrowband signals in broadband noise is considered. Successive systematic refinement of the wavelet coefficients is a feature of the iterative algorithm. The criterion for detecting narrowband signals via local maximums of the distribution of wavelet coefficients variance is proposed. The results of applying the algorithm to the test signals are presented. Models of discrete spectral components of the broadband noise were used as test signals. Screw propellers vessel can be sources of such noise. Two discrete spectral components were set for models. Negative signal-to-noise ratio was set to the level of - 6 dB. Distribution chart variance of the wavelet coefficients in the scales was constructed. Presence of a maximum in this chart was recognized as discrete spectral component detection. Wavelet known as the "Mexican hat" was chosen as the mother wavelet. The proposed algorithm allows to observe the emergence of peaks during data processing. This allows concluding about the detection before full processing over the entire sample. Time savings amounted to about 35 % of full processing of sample in this example. This result of the proposed algorithm is important in the problem of passive detection that don't show one's own presence in watery surroundings. Режим доступа: по договору с организацией-держателем ресурса |
| Jezik: | ruščina |
| Izdano: |
2014
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| Teme: | |
| Online dostop: | http://www.vkit.ru/index.php/archive-rus/276-017-022 http://elibrary.ru/item.asp?id=22014740 |
| Format: | Elektronski Book Chapter |
| KOHA link: | https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=645438 |
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| 200 | 1 | |a Применение итерационного алгоритма вейвлет-преобразования для обнаружения узкополосных сигналов |d Application of Iterative Algorithm Wavelet Transform for Detection of Narrowband Signals |f А. А. Хамухин | |
| 203 | |a Текст |c электронный | ||
| 300 | |a Заглавие с экрана | ||
| 320 | |a [Библиогр.: с. 22 (8 назв.)] | ||
| 330 | |a Рассмотрено применение итерационного алгоритма непрерывного вейвлет-преобразования для обнаружения узкополосных сигналов на фоне широкополосного шума. Предложено дополнение алгоритма критерием обнаружения узкополосных сигналов по локальным максимумам распределения дисперсии вейвлет-коэффициентов. Представлены результаты применения алгоритма на тестовых сигналах с отрицательным значением отношения сигнал/шум. | ||
| 330 | |a The application of the iterative algorithm for continuous wavelet transform for the detection of narrowband signals in broadband noise is considered. Successive systematic refinement of the wavelet coefficients is a feature of the iterative algorithm. The criterion for detecting narrowband signals via local maximums of the distribution of wavelet coefficients variance is proposed. The results of applying the algorithm to the test signals are presented. Models of discrete spectral components of the broadband noise were used as test signals. Screw propellers vessel can be sources of such noise. Two discrete spectral components were set for models. Negative signal-to-noise ratio was set to the level of - 6 dB. Distribution chart variance of the wavelet coefficients in the scales was constructed. Presence of a maximum in this chart was recognized as discrete spectral component detection. Wavelet known as the "Mexican hat" was chosen as the mother wavelet. The proposed algorithm allows to observe the emergence of peaks during data processing. This allows concluding about the detection before full processing over the entire sample. Time savings amounted to about 35 % of full processing of sample in this example. This result of the proposed algorithm is important in the problem of passive detection that don't show one's own presence in watery surroundings. | ||
| 333 | |a Режим доступа: по договору с организацией-держателем ресурса | ||
| 461 | |t Вестник компьютерных и информационных технологий |o научно-технический и производственный журнал |d 2004- | ||
| 463 | |t № 8 (122) |v [С. 17-22] |d 2014 | ||
| 510 | 1 | |a Methods of recording the location and traffic parameters of urban fixed-route transport according to satellite monitoring data |z eng | |
| 610 | 1 | |a электронный ресурс | |
| 610 | 1 | |a труды учёных ТПУ | |
| 610 | 1 | |a итерационные алгоритмы | |
| 610 | 1 | |a вейвлет-преобразования | |
| 610 | 1 | |a широкополосные сигналы | |
| 610 | 1 | |a дисперсия | |
| 700 | 1 | |a Хамухин |b А. А. |c специалист в области информатики и вычислительной техники |c доцент Томского политехнического университета, кандидат технических наук |f 1954- |g Александр Анатольевич |3 (RuTPU)RU\TPU\pers\24263 |9 10734 | |
| 712 | 0 | 2 | |a Национальный исследовательский Томский политехнический университет (ТПУ) |b Институт кибернетики (ИК) |b Кафедра автоматики и компьютерных систем (АИКС) |3 (RuTPU)RU\TPU\col\18698 |
| 801 | 2 | |a RU |b 63413507 |c 20151218 |g RCR | |
| 856 | 4 | |u http://www.vkit.ru/index.php/archive-rus/276-017-022 | |
| 856 | 4 | |u http://elibrary.ru/item.asp?id=22014740 | |
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