Synopsis
The applications of digitally modulated signals are still in progress and expansion. Automatic Modulation Identification (AMI) is important to classify the digitally modulated signals of arbitrary modulation schemes. AMI is crucial in military applications, like electronic surveillance, and interference recognition. In civil applications, AMI can be employed in Software Defined Radio (SDR), signal monitoring, intelligent modems, Cognitive Radio (CR), etc. This book therefore, provides a new metric of success for classification of the digitally modulated signals: Multi-user Chirp Spread Spectrum (CSS), 2FSK, 4FSK, 8FSK, 2PSK, 4PSK, 8PSK, 16QAM, 32QAM, 64QAM, 128QAM, and 256QAM signals, using MATLAB. The analysis should help shed some light on digitally modulated signals, adaptive neural fuzzy inference system (ANFIS), wavelet transform, high order statistics, signals classification approaches, and should be especially useful to professionals in communications and the newcomers to this field to determine the ability and limitation associated with the ANFIS based digitally modulated signal classification.
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About the Author
Hadi A. Hamed received the B.S in electrical engineering, Msc, Ph.D degrees in communication engineering from the University of Technology, Baghdad, in 1977, 2005, and 2017, respectively. He is a member of IEEE, and has altogether 9 international/ national journals/ conference,and author of chapter in a book published by CRC Press Taylor & Francis.
"About this title" may belong to another edition of this title.
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ANFIS Technique for Identification of Digitally Modulated Signals
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The applications of digitally modulated signals are still in progress and expansion. Automatic Modulation Identification (AMI) is important to classify the digitally modulated signals of arbitrary modulation schemes. AMI is crucial in military applications, like electronic surveillance, and interference recognition. In civil applications, AMI can be employed in Software Defined Radio (SDR), signal monitoring, intelligent modems, Cognitive Radio (CR), etc. This book therefore, provides a new metric of success for classification of the digitally modulated signals: Multi-user Chirp Spread Spectrum (CSS), 2FSK, 4FSK, 8FSK, 2PSK, 4PSK, 8PSK, 16QAM, 32QAM, 64QAM, 128QAM, and 256QAM signals, using MATLAB. The analysis should help shed some light on digitally modulated signals, adaptive neural fuzzy inference system (ANFIS), wavelet transform, high order statistics, signals classification approaches, and should be especially useful to professionals in communications and the newcomers to this field to determine the ability and limitation associated with the ANFIS based digitally modulated signal classification. 196 pp. Englisch. Seller Inventory # 9786202300520
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ANFIS Technique for Identification of Digitally Modulated Signals
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Hamed Hadi A.Hadi A. Hamed received the B.S in electrical engineering, Msc, Ph.D degrees in communication engineering from the University of Technology, Baghdad, in 1977, 2005, and 2017, respectively. He is a member of IEEE, and has . Seller Inventory # 169012629
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ANFIS Technique for Identification of Digitally Modulated Signals: Using MATLAB
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ANFIS Technique for Identification of Digitally Modulated Signals | Using MATLAB
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Taschenbuch. Condition: Neu. ANFIS Technique for Identification of Digitally Modulated Signals | Using MATLAB | Hadi A. Hamed (u. a.) | Taschenbuch | Englisch | 2017 | Scholars' Press | EAN 9786202300520 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Seller Inventory # 113379993
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ANFIS Technique for Identification of Digitally Modulated Signals
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ISBN 13: 9786202300520
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The applications of digitally modulated signals are still in progress and expansion. Automatic Modulation Identification (AMI) is important to classify the digitally modulated signals of arbitrary modulation schemes. AMI is crucial in military applications, like electronic surveillance, and interference recognition. In civil applications, AMI can be employed in Software Defined Radio (SDR), signal monitoring, intelligent modems, Cognitive Radio (CR), etc. This book therefore, provides a new metric of success for classification of the digitally modulated signals: Multi-user Chirp Spread Spectrum (CSS), 2FSK, 4FSK, 8FSK, 2PSK, 4PSK, 8PSK, 16QAM, 32QAM, 64QAM, 128QAM, and 256QAM signals, using MATLAB. The analysis should help shed some light on digitally modulated signals, adaptive neural fuzzy inference system (ANFIS), wavelet transform, high order statistics, signals classification approaches, and should be especially useful to professionals in communications and the newcomers to this field to determine the ability and limitation associated with the ANFIS based digitally modulated signal classification.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 196 pp. Englisch. Seller Inventory # 9786202300520
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ANFIS Technique for Identification of Digitally Modulated Signals : Using MATLAB
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The applications of digitally modulated signals are still in progress and expansion. Automatic Modulation Identification (AMI) is important to classify the digitally modulated signals of arbitrary modulation schemes. AMI is crucial in military applications, like electronic surveillance, and interference recognition. In civil applications, AMI can be employed in Software Defined Radio (SDR), signal monitoring, intelligent modems, Cognitive Radio (CR), etc. This book therefore, provides a new metric of success for classification of the digitally modulated signals: Multi-user Chirp Spread Spectrum (CSS), 2FSK, 4FSK, 8FSK, 2PSK, 4PSK, 8PSK, 16QAM, 32QAM, 64QAM, 128QAM, and 256QAM signals, using MATLAB. The analysis should help shed some light on digitally modulated signals, adaptive neural fuzzy inference system (ANFIS), wavelet transform, high order statistics, signals classification approaches, and should be especially useful to professionals in communications and the newcomers to this field to determine the ability and limitation associated with the ANFIS based digitally modulated signal classification. Seller Inventory # 9786202300520
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