Ghoraani behnaz (6 risultati)

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    • Lingua: Inglese

      Editore: LAP LAMBERT Academic Publishing, 2011

      3845435828 / 9783845435824

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      Da: preigu, Osnabrück, Germaniapreigu

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      Condizione: Nuovo

      EUR 66,50

      EUR 70,00 spedizione 
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      Quantità: 5 disponibili

      Taschenbuch. Condizione: Neu. Time-frequency Feature Analysis | Applications in Multimedia and Biomedical Signal Classification | Behnaz Ghoraani (u. a.) | Taschenbuch | 328 S. | Englisch | 2011 | LAP LAMBERT Academic Publishing | EAN 9783845435824 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.

    • Lingua: Inglese

      Editore: LAP LAMBERT Academic Publishing, 2011

      3845435828 / 9783845435824

      • Brossura

      Da: Mispah books, Redhill, SURRE, Regno UnitoMispah books

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      Condizione: Usato - Come nuovo

      EUR 175,02

      EUR 29,10 spedizione 
      Spedito da Regno Unito a U.S.A.

      Quantità: 1 disponibili

      Paperback. Condizione: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

    • Lingua: Inglese

      Editore: LAP LAMBERT Academic Publishing Aug 2011, 2011

      3845435828 / 9783845435824

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      Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.

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      Condizione: Nuovo

      EUR 79,00

      EUR 23,00 spedizione 
      Spedito da Germania a U.S.A.

      Quantità: 2 disponibili

      Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Signal processing can be found in many applications and its primary goal is to provide underlying information for the purpose of decision making. However, most of the real-world signals are challenging in nature as they are nonstationary, i.e., their statistics are time variant. Therefore, time or frequency descriptions, alone, are insufficient to provide comprehensive information about these challenging signals. On the contrary, extracting joint time-varying frequency characteristics of signals has an immense potential for revealing the nonstationary behaviour of signals better. This book is an attempt to develop a generalized time-frequency (TF) analysis methodology that exploits the benefits of TF distribution in pattern classification systems as related to discriminant feature detection and feature classification. This book describes the traditional TF feature analysis along with recently proposed approaches. The theoretical properties of these methods are examined. Additionally, advantages of these approaches in various applications such as feature extraction and automated-decision making systems are demonstrated through examples of different synthetic and real-world signals. 328 pp. Englisch.

    • Lingua: Inglese

      Editore: LAP LAMBERT Academic Publishing, 2011

      3845435828 / 9783845435824

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      Da: moluna, Greven, Germaniamoluna

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      Condizione: Nuovo

      EUR 63,42

      EUR 48,99 spedizione 
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      Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Ghoraani BehnazDr. Ghoraani is a PhD in Electrical and Computer Engineering. Her research interests center on time-frequency feature analysis, and Multimedia and Biomedical signal processing. Professor Krishnan is a Canada Resear.

    • Lingua: Inglese

      Editore: LAP LAMBERT Academic Publishing Aug 2011, 2011

      3845435828 / 9783845435824

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      Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000

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      Condizione: Nuovo

      EUR 79,00

      EUR 60,00 spedizione 
      Spedito da Germania a U.S.A.

      Quantità: 1 disponibili

      Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Signal processing can be found in many applications and its primary goal is to provide underlying information for the purpose of decision making. However, most of the real-world signals are challenging in nature as they are nonstationary, i.e., their statistics are time variant. Therefore, time or frequency descriptions, alone, are insufficient to provide comprehensive information about these challenging signals. On the contrary, extracting joint time-varying frequency characteristics of signals has an immense potential for revealing the nonstationary behaviour of signals better. This book is an attempt to develop a generalized time-frequency (TF) analysis methodology that exploits the benefits of TF distribution in pattern classification systems as related to discriminant feature detection and feature classification. This book describes the traditional TF feature analysis along with recently proposed approaches. The theoretical properties of these methods are examined. Additionally, advantages of these approaches in various applications such as feature extraction and automated-decision making systems are demonstrated through examples of different synthetic and real-world signals.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 328 pp. Englisch.

    • Lingua: Inglese

      Editore: LAP LAMBERT Academic Publishing, 2011

      3845435828 / 9783845435824

      • Brossura
      • Print on Demand

      Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH

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      Condizione: Nuovo

      EUR 79,00

      EUR 62,53 spedizione 
      Spedito da Germania a U.S.A.

      Quantità: 1 disponibili

      Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Signal processing can be found in many applications and its primary goal is to provide underlying information for the purpose of decision making. However, most of the real-world signals are challenging in nature as they are nonstationary, i.e., their statistics are time variant. Therefore, time or frequency descriptions, alone, are insufficient to provide comprehensive information about these challenging signals. On the contrary, extracting joint time-varying frequency characteristics of signals has an immense potential for revealing the nonstationary behaviour of signals better. This book is an attempt to develop a generalized time-frequency (TF) analysis methodology that exploits the benefits of TF distribution in pattern classification systems as related to discriminant feature detection and feature classification. This book describes the traditional TF feature analysis along with recently proposed approaches. The theoretical properties of these methods are examined. Additionally, advantages of these approaches in various applications such as feature extraction and automated-decision making systems are demonstrated through examples of different synthetic and real-world signals.