Isbn: 9783847340171 - sonar and radar signal classification: neural network based approaches (7 risultati)

Taschenbuch. Condizione: Neu. Sonar and Radar Signal Classification | Neural Network Based Approaches | Suresh Salankar (u. a.) | Taschenbuch | 140 S. | Englisch | 2012 | LAP LAMBERT Academic Publishing | EAN 9783847340171 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu. …

Condizione: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | In recent years neural computing has emerged as a practical technology, with successful applications in many fields. The use of neural networks in pattern classification is becoming increasingly widespread, with applications in signal processing areas such as signal detection and classification. In this book, the signals concerned include sonar and radar ionosphere databases from the research literature. These two data sets are intentionally chosen, because they contain high dimensionality, small sample sized problem and complex decision boundaries due to overlapping clusters. Learning from small sample sized dataset is typically a very difficult problem in the theory of complexity. It is a challenging task even for neural network. We have investigated the neural network based design of an optimal classifier and attempt is made to suggest suitable model by comparative analysis of the designed classifier for pattern classification on standard benchmark databases of sonar and radar ionosphere from the real world systems. …

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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In recent years neural computing has emerged as a practical technology, with successful applications in many fields. The use of neural networks in pattern classification is becoming increasingly widespread, with applications in signal processing areas such as signal detection and classification. In this book, the signals concerned include sonar and radar ionosphere databases from the research literature. These two data sets are intentionally chosen, because they contain high dimensionality, small sample sized problem and complex decision boundaries due to overlapping clusters. Learning from small sample sized dataset is typically a very difficult problem in the theory of complexity. It is a challenging task even for neural network. We have investigated the neural network based design of an optimal classifier and attempt is made to suggest suitable model by comparative analysis of the designed classifier for pattern classification on standard benchmark databases of sonar and radar ionosphere from the real world systems. 140 pp. Englisch.…

Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Salankar SureshSuresh Salankar:Ph.D., SRTM University Nanded. Presently working as Principal, J. L. Chaturvedi College of Engineering, Nagpur, India.Balasaheb Patre:Ph.D., IIT Bombay. Presently working as a Professor and Head, Depart. …

Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -In recent years neural computing has emerged as a practical technology, with successful applications in many fields. The use of neural networks in pattern classification is becoming increasingly widespread, with applications in signal processing areas such as signal detection and classification. In this book, the signals concerned include sonar and radar ionosphere databases from the research literature. These two data sets are intentionally chosen, because they contain high dimensionality, small sample sized problem and complex decision boundaries due to overlapping clusters. Learning from small sample sized dataset is typically a very difficult problem in the theory of complexity. It is a challenging task even for neural network. We have investigated the neural network based design of an optimal classifier and attempt is made to suggest suitable model by comparative analysis of the designed classifier for pattern classification on standard benchmark databases of sonar and radar ionosphere from the real world systems.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 140 pp. Englisch.…

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In recent years neural computing has emerged as a practical technology, with successful applications in many fields. The use of neural networks in pattern classification is becoming increasingly widespread, with applications in signal processing areas such as signal detection and classification. In this book, the signals concerned include sonar and radar ionosphere databases from the research literature. These two data sets are intentionally chosen, because they contain high dimensionality, small sample sized problem and complex decision boundaries due to overlapping clusters. Learning from small sample sized dataset is typically a very difficult problem in the theory of complexity. It is a challenging task even for neural network. We have investigated the neural network based design of an optimal classifier and attempt is made to suggest suitable model by comparative analysis of the designed classifier for pattern classification on standard benchmark databases of sonar and radar ionosphere from the real world systems. …