fuzzy based pseudo random von al karawi nagwan (7 Ergebnisse)

Zustand: New. pp. 76.

Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Al-karawi NagwanNagwan A. Al-Karawi,Studied Data Network Security in Al-Nahrian University, Assistant Lecturer in Al-Nahrian University,Baghdad,Iraq.Direct sequence spread spectrum uses a carrier that remains fixed to a specific .

Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Direct sequence spread spectrum uses a carrier that remains fixed to a specific frequency band. The data signal, rather than being transmitted on a narrow band as is done in microwave communications, is spread onto a much larger range of frequencies using a specific encoding scheme. This encoding scheme is known as a Pseudo Noise sequence. The algorithm used by the PN sequence generates a Pseudo Random Number Generator that is then combined, through a binary encoding process, with the binary information from the data stream. In this book, three conventional types of PRNG were implemented. These are linear feed back shift register, nonlinear feed back shift register and Blum Blum Shub generator. A fuzzy system is studied and Fuzzy based Pseudo Random Number Generator had been implemented to generate the frequency hopping sequences for spread spectrum communications system. Thirty sample patterns are the input to FPRNG, while the bandwidth is partitioned into number of frequency bins. Each bin used triangular membership function to analyze the input to fuzzy sets, encoding these as fuzzy rules. The input vector matches if-part of a fuzzy rule and fires that rule's output fuzzy set. 76 pp. Englisch.

Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Direct sequence spread spectrum uses a carrier that remains fixed to a specific frequency band. The data signal, rather than being transmitted on a narrow band as is done in microwave communications, is spread onto a much larger range of frequencies using a specific encoding scheme. This encoding scheme is known as a Pseudo Noise sequence. The algorithm used by the PN sequence generates a Pseudo Random Number Generator that is then combined, through a binary encoding process, with the binary information from the data stream. In this book, three conventional types of PRNG were implemented. These are linear feed back shift register, nonlinear feed back shift register and Blum Blum Shub generator. A fuzzy system is studied and Fuzzy based Pseudo Random Number Generator had been implemented to generate the frequency hopping sequences for spread spectrum communications system. Thirty sample patterns are the input to FPRNG, while the bandwidth is partitioned into number of frequency bins. Each bin used triangular membership function to analyze the input to fuzzy sets, encoding these as fuzzy rules. The input vector matches if-part of a fuzzy rule and fires that rule's output fuzzy set.

Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Direct sequence spread spectrum uses a carrier that remains fixed to a specific frequency band. The data signal, rather than being transmitted on a narrow band as is done in microwave communications, is spread onto a much larger range of frequencies using a specific encoding scheme. This encoding scheme is known as a Pseudo Noise sequence. The algorithm used by the PN sequence generates a Pseudo Random Number Generator that is then combined, through a binary encoding process, with the binary information from the data stream. In this book, three conventional types of PRNG were implemented. These are linear feed back shift register, nonlinear feed back shift register and Blum Blum Shub generator. A fuzzy system is studied and Fuzzy based Pseudo Random Number Generator had been implemented to generate the frequency hopping sequences for spread spectrum communications system. Thirty sample patterns are the input to FPRNG, while the bandwidth is partitioned into number of frequency bins. Each bin used triangular membership function to analyze the input to fuzzy sets, encoding these as fuzzy rules. The input vector matches if-part of a fuzzy rule and fires that rule¿s output fuzzy set.Books on Demand GmbH, Überseering 33, 22297 Hamburg 76 pp. Englisch.

Zustand: New. PRINT ON DEMAND pp. 76.

Zustand: New. Print on Demand pp. 76 2:B&W 6 x 9 in or 229 x 152 mm Perfect Bound on Creme w/Gloss Lam.