This thesis proposes an approach for modulation classification using existing features in a more efficient way. The Multi-Dimensional Classification Algorithm (MDCA) treats features extracted from signals of interest as elements with irrelevant identities, hence eliminating any dependence of the classifier on any particular feature. This design enables the use of any number of features, and the MDCA algorithm provides the capability to classify modulations in higher dimensions. The use of multiple features requires an equal number of data dimensions, and thus classification in as high a dimensional space as possible can improve final classification results. Finally, the MDCA algorithm uses a relatively small number of simple operations, which leads to a fast processing time. Simulation results for the MDCA algorithm demonstrate good potential. In particular, the MDCA consistently performed well (at SNR levels down to -10dB in some cases) and in identifying more modulation types.
Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.
Anbieter: Lucky's Textbooks, Dallas, TX, USA
Zustand: New. Bestandsnummer des Verkäufers ABLIING23Mar2411530031860
Anzahl: Mehr als 20 verfügbar
Anbieter: PBShop.store US, Wood Dale, IL, USA
PAP. Zustand: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Bestandsnummer des Verkäufers L0-9781288326761
Anzahl: Mehr als 20 verfügbar
Anbieter: PBShop.store UK, Fairford, GLOS, Vereinigtes Königreich
PAP. Zustand: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Bestandsnummer des Verkäufers L0-9781288326761
Anzahl: Mehr als 20 verfügbar
Anbieter: Books Puddle, New York, NY, USA
Zustand: New. pp. 142. Bestandsnummer des Verkäufers 26390601220
Anzahl: 4 verfügbar
Anbieter: Majestic Books, Hounslow, Vereinigtes Königreich
Zustand: New. Print on Demand pp. 142. Bestandsnummer des Verkäufers 390047195
Anzahl: 4 verfügbar
Anbieter: THE SAINT BOOKSTORE, Southport, Vereinigtes Königreich
Paperback / softback. Zustand: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days. Bestandsnummer des Verkäufers C9781288326761
Anzahl: Mehr als 20 verfügbar
Anbieter: Biblios, Frankfurt am main, HESSE, Deutschland
Zustand: New. PRINT ON DEMAND pp. 142. Bestandsnummer des Verkäufers 18390601230
Anzahl: 4 verfügbar
Anbieter: moluna, Greven, Deutschland
Zustand: New. This thesis proposes an approach for modulation classification using existing features in a more efficient way. The Multi-Dimensional Classification Algorithm (MDCA) treats features extracted from signals of interest as elements with irrelevant identities, . Bestandsnummer des Verkäufers 6555642
Anzahl: Mehr als 20 verfügbar
Anbieter: Mispah books, Redhill, SURRE, Vereinigtes Königreich
Paperback. Zustand: Like New. Like New. book. Bestandsnummer des Verkäufers ERICA79612883267696
Anzahl: 1 verfügbar
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Taschenbuch. Zustand: Neu. Neuware - This thesis proposes an approach for modulation classification using existing features in a more efficient way. The Multi-Dimensional Classification Algorithm (MDCA) treats features extracted from signals of interest as elements with irrelevant identities, hence eliminating any dependence of the classifier on any particular feature. This design enables the use of any number of features, and the MDCA algorithm provides the capability to classify modulations in higher dimensions. The use of multiple features requires an equal number of data dimensions, and thus classification in as high a dimensional space as possible can improve final classification results. Finally, the MDCA algorithm uses a relatively small number of simple operations, which leads to a fast processing time. Simulation results for the MDCA algorithm demonstrate good potential. In particular, the MDCA consistently performed well (at SNR levels down to -10dB in some cases) and in identifying more modulation types. Bestandsnummer des Verkäufers 9781288326761
Anzahl: 2 verfügbar