An Algorithm of Daubechies Wavelet Transform in the Final Field When Processing Speech Signals

Development and improvement of a mathematical model for a large-scale analysis based on the Daubechies discrete wavelet transform will be implemented in an algebraic system possessing a property of ring and field suitable for speech signals processing. Modular codes are widely used in many areas of...

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Main Authors:	Dmitry Popov, Artem Gapochkin, Alexey Nekrasov
Format:	Article
Language:	English
Published:	MDPI AG 2018-07-01
Series:	Electronics
Subjects:	modular codes large-scale signal processing wavelet transform Daubechies basic functions of Daubechies
Online Access:	http://www.mdpi.com/2079-9292/7/7/120

id	doaj-6e2c6b3b935a47d3bbd751abc154b2c5
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spelling	doaj-6e2c6b3b935a47d3bbd751abc154b2c52020-11-25T02:35:45ZengMDPI AGElectronics2079-92922018-07-017712010.3390/electronics7070120electronics7070120An Algorithm of Daubechies Wavelet Transform in the Final Field When Processing Speech SignalsDmitry Popov0Artem Gapochkin1Alexey Nekrasov2Department of Informatics and Information Technologies, Moscow Polytechnic University, Bolshaya Semenovskaya 38, Moscow 107023, RussiaDepartment of Informatics and Information Technologies, Moscow Polytechnic University, Bolshaya Semenovskaya 38, Moscow 107023, RussiaInstitute for Computer Technologies and Information Security, Southern Federal University, Chekhova 2, Taganrog 347922, RussiaDevelopment and improvement of a mathematical model for a large-scale analysis based on the Daubechies discrete wavelet transform will be implemented in an algebraic system possessing a property of ring and field suitable for speech signals processing. Modular codes are widely used in many areas of modern information technologies. The use of these non-positional codes can provide high-speed data processing. Therefore, these algebraic systems should be used in the algorithms of digital processing of signals, which are characterized by processing large amounts of data in real time. In addition, modular codes make it possible to implement large-scale signal processing using the wavelet transform. The paper discusses examples of the Daubechies wavelet transform application. Integer processing, presented in the paper, will reduce the number of rounding errors when processing the speech signals.http://www.mdpi.com/2079-9292/7/7/120modular codeslarge-scale signal processingwavelet transform Daubechiesbasic functions of Daubechies
collection	DOAJ
language	English
format	Article
sources	DOAJ
author	Dmitry Popov Artem Gapochkin Alexey Nekrasov
spellingShingle	Dmitry Popov Artem Gapochkin Alexey Nekrasov An Algorithm of Daubechies Wavelet Transform in the Final Field When Processing Speech Signals Electronics modular codes large-scale signal processing wavelet transform Daubechies basic functions of Daubechies
author_facet	Dmitry Popov Artem Gapochkin Alexey Nekrasov
author_sort	Dmitry Popov
title	An Algorithm of Daubechies Wavelet Transform in the Final Field When Processing Speech Signals
title_short	An Algorithm of Daubechies Wavelet Transform in the Final Field When Processing Speech Signals
title_full	An Algorithm of Daubechies Wavelet Transform in the Final Field When Processing Speech Signals
title_fullStr	An Algorithm of Daubechies Wavelet Transform in the Final Field When Processing Speech Signals
title_full_unstemmed	An Algorithm of Daubechies Wavelet Transform in the Final Field When Processing Speech Signals
title_sort	algorithm of daubechies wavelet transform in the final field when processing speech signals
publisher	MDPI AG
series	Electronics
issn	2079-9292
publishDate	2018-07-01
description	Development and improvement of a mathematical model for a large-scale analysis based on the Daubechies discrete wavelet transform will be implemented in an algebraic system possessing a property of ring and field suitable for speech signals processing. Modular codes are widely used in many areas of modern information technologies. The use of these non-positional codes can provide high-speed data processing. Therefore, these algebraic systems should be used in the algorithms of digital processing of signals, which are characterized by processing large amounts of data in real time. In addition, modular codes make it possible to implement large-scale signal processing using the wavelet transform. The paper discusses examples of the Daubechies wavelet transform application. Integer processing, presented in the paper, will reduce the number of rounding errors when processing the speech signals.
topic	modular codes large-scale signal processing wavelet transform Daubechies basic functions of Daubechies
url	http://www.mdpi.com/2079-9292/7/7/120
work_keys_str_mv	AT dmitrypopov analgorithmofdaubechieswavelettransforminthefinalfieldwhenprocessingspeechsignals AT artemgapochkin analgorithmofdaubechieswavelettransforminthefinalfieldwhenprocessingspeechsignals AT alexeynekrasov analgorithmofdaubechieswavelettransforminthefinalfieldwhenprocessingspeechsignals AT dmitrypopov algorithmofdaubechieswavelettransforminthefinalfieldwhenprocessingspeechsignals AT artemgapochkin algorithmofdaubechieswavelettransforminthefinalfieldwhenprocessingspeechsignals AT alexeynekrasov algorithmofdaubechieswavelettransforminthefinalfieldwhenprocessingspeechsignals
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An Algorithm of Daubechies Wavelet Transform in the Final Field When Processing Speech Signals

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