Reduce the noise in speech signals using wavelet filtering
Author
Source
Journal of University of Babylon for Engineering Sciences
Issue
Vol. 26, Issue 5 (31 May. 2018), pp.157-165, 9 p.
Publisher
Publication Date
2018-05-31
Country of Publication
Iraq
No. of Pages
9
Main Subjects
Abstract EN
Friction stir welding (FSW) is proved as a promising welding technology for joining dissimilar aluminium alloys.
Aluminium alloys are used extensively within the aerospace industry for applications such as fuselage and wing skin panels due to their high strength to weight ratio.
Therefore, an effort is made to optimize the process parameters of FSW using Al 6061 and Al 7075 alloys by the Minitab 16 program in order to enhance tensile properties such as elongation (E), yield stress (YS), and ultimate tensile strength (UTS).
Grey relational analysis (GRA) based on the Taguchi method is applied using two factors tool rotational speeds (TRS) and welding speed (WS) with four levels.
Results show that the variables, namely the tool rotation speed and welding speed have a significant effect on yield stress, ultimate tensile strength and elongation.
Results also show that the Taguchi based grey relational approach improved properties of output response of welded Al 6061 and Al 7075 aluminum alloys.
American Psychological Association (APA)
Laftah, Husayn Ali. 2018. Reduce the noise in speech signals using wavelet filtering. Journal of University of Babylon for Engineering Sciences،Vol. 26, no. 5, pp.157-165.
https://search.emarefa.net/detail/BIM-923610
Modern Language Association (MLA)
Laftah, Husayn Ali. Reduce the noise in speech signals using wavelet filtering. Journal of University of Babylon for Engineering Sciences Vol. 26, no. 5 (2018), pp.157-165.
https://search.emarefa.net/detail/BIM-923610
American Medical Association (AMA)
Laftah, Husayn Ali. Reduce the noise in speech signals using wavelet filtering. Journal of University of Babylon for Engineering Sciences. 2018. Vol. 26, no. 5, pp.157-165.
https://search.emarefa.net/detail/BIM-923610
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 164-165
Record ID
BIM-923610