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SELECTION OF DELTA FUNCTION WAVEFORM AND ITS PARAMETERS FOR OPTIMAL DISCRETE WAVELET TRANSFORM APPLICATION TO INPUT SIGNALS BASED ON THEIR PURPOSE

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dc.contributor.authorQalandarov Jo'rabek To'khtamirzayev
dc.contributor.authorKhakimov Ilhomjon Olimjon oglu
dc.contributor.authorTohirjonova Muattarkhon Rasuljon qizi
dc.contributor.authorAhmadjonova Madinabonu Khasanboy qizi
dc.contributor.authorSharipbayev Sobitkhon Sobir oglu
dc.contributor.authorReutskaya Olga Gennadievna
dc.date.accessioned2026-02-26T20:30:27Z
dc.date.issued2026-02-26
dc.description.abstractThe discrete wavelet transform (DWT) stands out as one of the most powerful techniques for analyzing non-stationary signals across time and scale domains. Sensor signals like vibration, acoustic, current-voltage, medical (ECG/EEG), and others captured in real-world systems typically feature noise, transient events (impulses, jumps, discontinuities), and gradual trends. Thus, selecting the appropriate wavelet type and its parameters during processing critically determines the output's precision and reliability.
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dc.identifier.urihttps://usajournals.org/index.php/2/article/view/2016
dc.identifier.urihttps://asianeducationindex.com/handle/123456789/117101
dc.language.isoeng
dc.publisherModern American Journals
dc.relationhttps://usajournals.org/index.php/2/article/view/2016/2098
dc.rightshttps://creativecommons.org/licenses/by/4.0
dc.sourceModern American Journal of Engineering, Technology, and Innovation; Vol. 2 No. 2 (2026); 20-35
dc.source3067-7939
dc.subjectDiscrete wavelet transform, wavelet selection, impulse (delta), denoising, threshold, decomposition level, feature extraction, compression, diagnostics.
dc.titleSELECTION OF DELTA FUNCTION WAVEFORM AND ITS PARAMETERS FOR OPTIMAL DISCRETE WAVELET TRANSFORM APPLICATION TO INPUT SIGNALS BASED ON THEIR PURPOSE
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion
dc.typePeer-reviewed Article

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Modern American Journal of Engineering, Technology, and Innovation