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001 978-1-4939-0588-1
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005 20200421112221.0
007 cr nn 008mamaa
008 140321s2014 xxu| s |||| 0|eng d
020 _a9781493905881
_9978-1-4939-0588-1
024 7 _a10.1007/978-1-4939-0588-1
_2doi
050 4 _aTK5105.5-5105.9
072 7 _aUKN
_2bicssc
072 7 _aCOM075000
_2bisacsh
082 0 4 _a004.6
_223
100 1 _aGuang, Xuan.
_eauthor.
245 1 0 _aLinear Network Error Correction Coding
_h[electronic resource] /
_cby Xuan Guang, Zhen Zhang.
264 1 _aNew York, NY :
_bSpringer New York :
_bImprint: Springer,
_c2014.
300 _aVI, 107 p. 9 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSpringerBriefs in Computer Science,
_x2191-5768
505 0 _aIntroduction -- Network Error Correction Model -- Another Description of Linear Network Error Correction Model -- Coding Bounds of Linear Network Error Correction Codes -- Random Linear Network Error Correction Coding -- Subspace Codes.
520 _aThere are two main approaches in the theory of network error correction coding. In this SpringerBrief, the authors summarize some of the most important contributions following the classic approach, which represents messages by sequences similar to algebraic coding, and also briefly discuss the main results following the other approach, that uses the theory of rank metric codes for network error correction of representing messages by subspaces. This book starts by establishing the basic linear network error correction (LNEC) model and then characterizes two equivalent descriptions. Distances and weights are defined in order to characterize the discrepancy of these two vectors and to measure the seriousness of errors. Similar to classical error-correcting codes, the authors also apply the minimum distance decoding principle to LNEC codes at each sink node, but use distinct distances. For this decoding principle, it is shown that the minimum distance of a LNEC code at each sink node can fully characterize its error-detecting, error-correcting and erasure-error-correcting capabilities with respect to the sink node. In addition, some important and useful coding bounds in classical coding theory are generalized to linear network error correction coding, including the Hamming bound, the Gilbert-Varshamov bound and the Singleton bound. Several constructive algorithms of LNEC codes are presented, particularly for LNEC MDS codes, along with an analysis of their performance. Random linear network error correction coding is feasible for noncoherent networks with errors. Its performance is investigated by estimating upper bounds on some failure probabilities by analyzing the information transmission and error correction. Finally, the basic theory of subspace codes is introduced including the encoding and decoding principle as well as the channel model, the bounds on subspace codes, code construction and decoding algorithms.
650 0 _aComputer science.
650 0 _aComputer communication systems.
650 0 _aCoding theory.
650 1 4 _aComputer Science.
650 2 4 _aComputer Communication Networks.
650 2 4 _aCoding and Information Theory.
700 1 _aZhang, Zhen.
_eauthor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9781493905874
830 0 _aSpringerBriefs in Computer Science,
_x2191-5768
856 4 0 _uhttp://dx.doi.org/10.1007/978-1-4939-0588-1
912 _aZDB-2-SCS
942 _cEBK
999 _c57412
_d57412