Transactions on Computational Science XXIX (eBook, PDF)

Redaktion: Gavrilova, Marina L.; Tan, C. J. Kenneth

• Format: PDF

Produktbeschreibung

The LNCS journal Transactions on Computational Science reflects recent developments in the field of Computational Science, conceiving the field not as a mere ancillary science but rather as an innovative approach supporting many other scientific disciplines. The journal focuses on original high-quality research in the realm of computational science in parallel and distributed environments, encompassing the facilitating theoretical foundations and the applications of large-scale computations and massive data processing. It addresses researchers and practitioners in areas ranging from aerospace to biochemistry, from electronics to geosciences, from mathematics to software architecture, presenting verifiable computational methods, findings, and solutions, and enabling industrial users to apply techniques of leading-edge, large-scale, high performance computational methods.

This, the 29th issue of the Transactions on Computational Science journal, is comprised of seven full papers focusing on the area of secure communication. Topics covered include weak radio signals, efficient circuits, multiple antenna sensing techniques, modes of inter-computer communication and fault types, geometric meshes, and big data processing in distributed environments.

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Produktdetails

• Verlag: Springer Berlin Heidelberg
• Seitenzahl: 139
• Erscheinungstermin: 11. März 2017
• Englisch
• ISBN-13: 9783662545638
• Artikelnr.: 53061542

Autorenporträt

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Inhaltsangabe

Analysis of Relationship between Modes of Intercomputer Communications and Fault Types in Redundant Computer Systems.- Efficient Circuit Design of Reversible Square.- Methods of Registration of Weak Radio Signals.- A Novel Multiple Antennas Based Centralized Spectrum Sensing Technique.- ImatiSTL - Fast and Reliable Mesh Processing with a Hybrid Kernel.- Processing Large Geometric Datasets in Distributed Environments.- Decision Fusion for Classification of Content Based Image Data.