| Document Type
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BL
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| Record Number
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968014
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| Doc. No
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b722384
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| Main Entry
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Azzouz, Elsayed Elsayed.
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| Title & Author
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Automatic modulation recognition of communication signals /\ by Elsayed Elsayed Azzouz and Asoke Kumar Nandi.
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| Publication Statement
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Boston :: Kluwer Academic Publishers,, ©1996.
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| Page. NO
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xviii, 217 pages :: illustrations ;; 25 cm
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| ISBN
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0792397967
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: 9780792397960
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| Bibliographies/Indexes
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Includes bibliographical references (pages 182-186) and index.
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| Contents
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1. Introduction -- 2. Recognition of Analogue Modulations -- 3. Recognition of Digital Modulations -- 4. Recognition of Analogue & Digital Modulations -- 5. Modulation Recognition Using Artificial Neural Networks -- 6. Summary and Suggestions for Future Directions -- A. Numerical problems associated with the evaluation of the instantaneous amplitude, phase and frequency -- B. Carrier frequency estimation -- C. Alternative Algorithms for Modulation Recognition.
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| Abstract
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Automatic modulation recognition is a rapidly evolving area of signal analysis. In recent years, interest from the academic and military research institutes has focused around the research and development of modulation recognition algorithms. Any communication intelligence (COMINT) system comprises three main blocks: receiver front-end, modulation recogniser and output stage. Considerable work has been done in the area of receiver front-ends. The work at the output stage is concerned with information extraction, recording and exploitation and begins with signal demodulation, that requires accurate knowledge about the signal modulation type. There are, however, two main reasons for knowing the correct modulation type of a signal: to preserve the signal information content and to decide upon the suitable counter action, such as jamming. Automatic Modulation Recognition of Communication Signals describes in depth this modulation recognition process.
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Drawing on several years of research, the authors provide a critical review of automatic modulation recognition. This includes techniques for recognising digitally modulated signals. The book also gives comprehensive treatment of using artificial neural networks for recognising modulation types.
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| Subject
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Modulation (Electronics)
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Neural networks (Computer science)
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Pattern recognition systems.
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Signal processing.
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Modulation (Electronics)
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Neural networks (Computer science)
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Pattern recognition systems.
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| Subject
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Signal processing.
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| Subject
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Modulation.
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| Subject
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Neuronales Netz.
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| Subject
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Signalverarbeitung.
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| Dewey Classification
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621.382/23
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| LC Classification
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TK5102.9.A98 1996
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| NLM classification
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53.70bcl
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ZN 6130rvk
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| Added Entry
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Nandi, Asoke Kumar.
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