Titlebook: Schrift und Sprache der Chinesen; Bernhard Karlgren,Ulrich Klodt,Karl Frisch Book 19751st edition Springer-Verlag Berlin Heidelberg 1975 C

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Bernhard Karlgrenen propose an optimal power allocation algorithm for all D2D users and CUs by taking into account the property of non-negative inverse of a Z-matrix. The proposed algorithm is validated through simulation results which show the impacts of noise power, distance between D2D users, the number of D2D pa

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Bernhard KarlgrenXimum Value for the average end-to-end PNSC (MAXV) is selected for data transmission. Third, we also propose a RAND method in which a RANDom path is employed. For performance evaluation and comparison, we derive exact closed-form expressions for the end-to-end PNSC of the BEST, MAXV and RAND methods

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Bernhard Karlgrenen propose an optimal power allocation algorithm for all D2D users and CUs by taking into account the property of non-negative inverse of a Z-matrix. The proposed algorithm is validated through simulation results which show the impacts of noise power, distance between D2D users, the number of D2D pa

BALK

Bernhard Karlgreninvestigate the secrecy performance of this considered system according to key parameters, such as power allocation ratio, average transmit power and number of user pair to verify our proposed scheme. Finally, Monte- Carlo simulation results are provided to confirm the correctness of the analytical

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Bernhard Karlgreneural network accelerator on FPGA for MNIST and CIFAR-10 dataset. The major results indicate that the hardware design outperforms by at least 1500 times when the parallel coefficient . is 1 and maybe faster up to 20,000 times when that is 16 compared to the implementation on the software while the a

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rone communication due to the characteristics of wireless networks and mobility of drones. Our model consists of Searching & Finding and Functional Sub-layers. In the Searching & Finding Sub-layer, we locate the other drones in the air with a specific flying pattern; we also sense and collect frame

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