Separation and Classification of Different Musical Instruments Sound
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Von Händler/Antiquariat, The Book Depository EURO [60485773], London, United Kingdom.
Language: English Brand New Book ***** Print on Demand *****.Musical instrument separation uses a source separation approach that aims to separate the individual source instruments from a mixture of sound signal i.e song. This work uses mixtures of two instruments guitar and flute, having same pitch at the same time. In this work, the degenerate blind source separation(DBSS) is modified and it is used for machine learning problem. This approach is applied to separate the instrument sounds. Further on the musical instrument sounds i.e separated signals are classified individually with Fuzzy approach. Temporal, spectral and cepstral features are extracted for instrument classification out of detected monophonic musical signals. Here, supervised fuzzy classification is used for instrument classification. The book is of interest for music and speech signal researchers.

Von Händler/Antiquariat, AHA-BUCH GmbH [51283250], Einbeck, Germany.
This item is printed on demand - Print on Demand Titel. Neuware - Musical instrument separation uses a source separation approach that aims to separate the individual source instruments from a mixture of sound signal i.e song. This work uses mixtures of two instruments guitar and flute, having same pitch at the same time. In this work, the degenerate blind source separation(DBSS) is modified and it is used for machine learning problem. This approach is applied to separate the instrument sounds. Further on the musical instrument sounds i.e separated signals are classified individually with Fuzzy approach. Temporal, spectral and cepstral features are extracted for instrument classification out of detected monophonic musical signals. Here, supervised fuzzy classification is used for instrument classification. The book is of interest for music and speech signal researchers. 128 pp. Englisch.

Lieferung aus: Deutschland, zzgl. Versandkosten.
Musical instrument separation uses a source separation approach that aims to separate the individual source instruments from a mixture of sound signal i.e song. This work uses mixtures of two instruments guitar and flute, having same pitch at the same time. In this work, the degenerate blind source separation(DBSS) is modified and it is used for machine learning problem. This approach is applied to separate the instrument sounds. Further on the musical instrument sounds i.e separated signals are classified individually with Fuzzy approach. Temporal, spectral and cepstral features are extracted for instrument classification out of detected monophonic musical signals. Here, supervised fuzzy classification is used for instrument classification. The book is of interest for music and speech signal researchers.

Lieferung aus: Schweiz, Lieferzeit: 2 Tage, zzgl. Versandkosten.
Musical instrument separation uses a source separation approach that aims to separate the individual source instruments from a mixture of sound signal i.e song. This work uses mixtures of two instruments guitar and flute, having same pitch at the same time. In this work, the degenerate blind source separation(DBSS) is modified and it is used for machine learning problem. This approach is applied to separate the instrument sounds. Further on the musical instrument sounds i.e separated signals are classified individually with Fuzzy approach. Temporal, spectral and cepstral features are extracted for instrument classification out of detected monophonic musical signals. Here, supervised fuzzy classification is used for instrument classification. The book is of interest for music and speech signal researchers.

Lieferung aus: Deutschland, Versandkostenfrei.
Separation and Classification of Different Musical Instruments Sound: Musical instrument separation uses a source separation approach that aims to separate the individual source instruments from a mixture of sound signal i.e song. This work uses mixtures of two instruments guitar and flute, having same pitch at the same time. In this work, the degenerate blind source separation(DBSS) is modified and it is used for machine learning problem. This approach is applied to separate the instrument sounds. Further on the musical instrument sounds i.e separated signals are classified individually with Fuzzy approach. Temporal, spectral and cepstral features are extracted for instrument classification out of detected monophonic musical signals. Here, supervised fuzzy classification is used for instrument classification. The book is of interest for music and speech signal researchers. Englisch, Taschenbuch.

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Smita Silk, Solanki Sandeep Singh, Paperback, English-language edition, Pub by OmniScriptum GmbH & Co. KG.