000 04059nam a22005295i 4500
001 978-3-319-05479-7
003 DE-He213
005 20200421112048.0
007 cr nn 008mamaa
008 140508s2014 gw | s |||| 0|eng d
020 _a9783319054797
_9978-3-319-05479-7
024 7 _a10.1007/978-3-319-05479-7
_2doi
050 4 _aQ350-390
050 4 _aQA10.4
072 7 _aPBW
_2bicssc
072 7 _aMAT003000
_2bisacsh
082 0 4 _a519
_223
100 1 _aAhlswede, Rudolf.
_eauthor.
245 1 0 _aStoring and Transmitting Data
_h[electronic resource] :
_bRudolf Ahlswede's Lectures on Information Theory 1 /
_cby Rudolf Ahlswede ; edited by Alexander Ahlswede, Ingo Alth�ofer, Christian Deppe, Ulrich Tamm.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2014.
300 _aX, 302 p. 6 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aFoundations in Signal Processing, Communications and Networking,
_x1863-8538 ;
_v10
505 0 _aWords and Introduction of the Editors -- Preface -- 1.Introduction -- Part I Storing Data: 2.Data Compression -- 3.The Entropy as a Measure of Uncertainty -- 4.Universal Coding.- Part II Transmitting Data: 5.Coding Theorems and Converses for the DMC -- 6.Towards Capacity Functions -- 7.Error Bounds -- Part III Appendix: 8.Inequalities -- Part IV Supplement: Rudolf Ahlswede 1938-2010 -- Comments by Holger Boche -- Index -- Name Index.
520 _aThe volume "Storing and Transmitting Data" is based on Rudolf Ahlswede's introductory course on "Information Theory I" and presents an introduction to Shannon Theory. Readers, familiar or unfamiliar with the technical intricacies of Information Theory, will benefit considerably from working through the book; especially Chapter VI with its lively comments and uncensored insider views from the world of science and research offers informative and revealing insights. This is the first of several volumes that will serve as a collected research documentation of Rudolf Ahlswede's lectures on information theory. Each volume includes comments from an invited well-known expert. Holger Boche contributed his insights in the supplement of the present volume. Classical information processing concerns the main tasks of gaining knowledge, storage, transmitting and hiding data. The first task is the prime goal of Statistics. For the two next, Shannon presented an impressive mathematical theory called Information Theory, which he based on probabilistic models. The theory largely involves the concept of codes with small error probabilities in spite of noise in the transmission, which is modeled by channels. The lectures presented in this work are suitable for graduate students in Mathematics, and also in Theoretical Computer Science, Physics, and Electrical Engineering with background in basic Mathematics. The lectures can be used as the basis for courses or to supplement courses in many ways. Ph.D. students will also find research problems, often with conjectures, that offer potential subjects for a thesis. More advanced researchers may find the basis of entire research programs.
650 0 _aMathematics.
650 0 _aCoding theory.
650 0 _aInformation theory.
650 1 4 _aMathematics.
650 2 4 _aInformation and Communication, Circuits.
650 2 4 _aCoding and Information Theory.
700 1 _aAhlswede, Alexander.
_eeditor.
700 1 _aAlth�ofer, Ingo.
_eeditor.
700 1 _aDeppe, Christian.
_eeditor.
700 1 _aTamm, Ulrich.
_eeditor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783319054780
830 0 _aFoundations in Signal Processing, Communications and Networking,
_x1863-8538 ;
_v10
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-319-05479-7
912 _aZDB-2-ENG
942 _cEBK
999 _c57058
_d57058