The use of classification algorithms to automatically classify musical instruments is a current and ongoing research. Musical instruments classification has many applications such as cataloging of sound samples, music transcription and annotation system. Though, audio classification comprise of interdisciplinary areas namely data mining, signal processing and musicology. Meanwhile, soft set theory has emerged as a new mathematical tool that has high potential to be applied in many directions. However, soft set for musical instrument classification has not been widely experimented although this method is very reliable in handling texture classification and for data analysis efficiently. Thus, this book provides a classification algorithm based on soft set incorporating Traditional Pakistani musical instruments and offers a new perspective for automatic musical instrument classification.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
The use of classification algorithms to automatically classify musical instruments is a current and ongoing research. Musical instruments classification has many applications such as cataloging of sound samples, music transcription and annotation system. Though, audio classification comprise of interdisciplinary areas namely data mining, signal processing and musicology. Meanwhile, soft set theory has emerged as a new mathematical tool that has high potential to be applied in many directions. However, soft set for musical instrument classification has not been widely experimented although this method is very reliable in handling texture classification and for data analysis efficiently. Thus, this book provides a classification algorithm based on soft set incorporating Traditional Pakistani musical instruments and offers a new perspective for automatic musical instrument classification.
Saima Anwar Lashari is a PhD student at Universiti Tun Hussein Onn Malaysia (UTHM). Her research interests are in the field of signal and image processing, data mining and soft set.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Lashari Saima AnwarSaima Anwar Lashari is a PhD student at Universiti Tun Hussein Onn Malaysia (UTHM). Her research interests are in the field of signal and image processing, data mining and soft set.The use of classification alg. N° de réf. du vendeur 5473637
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Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The use of classification algorithms to automatically classify musical instruments is a current and ongoing research. Musical instruments classification has many applications such as cataloging of sound samples, music transcription and annotation system. Though, audio classification comprise of interdisciplinary areas namely data mining, signal processing and musicology. Meanwhile, soft set theory has emerged as a new mathematical tool that has high potential to be applied in many directions. However, soft set for musical instrument classification has not been widely experimented although this method is very reliable in handling texture classification and for data analysis efficiently. Thus, this book provides a classification algorithm based on soft set incorporating Traditional Pakistani musical instruments and offers a new perspective for automatic musical instrument classification. N° de réf. du vendeur 9783844332605
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Taschenbuch. Etat : Neu. Classification of Pakistani Musical Instruments Using Soft Set | Saima Anwar Lashari (u. a.) | Taschenbuch | Englisch | LAP Lambert Academic Publishing | EAN 9783844332605 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. N° de réf. du vendeur 106143050
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