LEADER 04165nam 22006615 450 001 9910874667003321 005 20240723130741.0 010 $a9783662691021$b(electronic bk.) 010 $z9783662691014 024 7 $a10.1007/978-3-662-69102-1 035 $a(MiAaPQ)EBC31545395 035 $a(Au-PeEL)EBL31545395 035 $a(CKB)33329814100041 035 $a(DE-He213)978-3-662-69102-1 035 $a(EXLCZ)9933329814100041 100 $a20240723d2024 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aMathematics of Information $eTheory and Applications of Shannon-Wiener Information /$fby Stefan Schäffler 205 $a1st ed. 2024. 210 1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d2024. 215 $a1 online resource (154 pages) 225 1 $aMathematics Study Resources,$x2731-3832 ;$v9 311 08$aPrint version: Schäffler, Stefan Mathematics of Information Berlin, Heidelberg : Springer Berlin / Heidelberg,c2024 9783662691014 327 $aIntroduction - Symbols - List of figures - Part I Fundamentals. Message and information -- Information and chance -- Part II Countable systems. The entropy -- The maximum entropy principle -- Conditional probabilities -- Quantum information -- Part III General systems -- The entropy of partitions -- Stationary information sources -- Density functions and entropy -- Conditional expectations -- Literature -- Index. 330 $aStarting with the Shannon-Wiener approach to mathematical information theory, allowing a mathematical "measurement" of an amount of information, the book begins by defining the terms message and information and axiomatically assigning an amount of information to a probability. The second part explores countable probability spaces, leading to the definition of Shannon entropy based on the average amount of information; three classical applications of Shannon entropy in statistical physics, mathematical statistics, and communication engineering are presented, along with an initial glimpse into the field of quantum information. The third part is dedicated to general probability spaces, focusing on the information-theoretical analysis of dynamic systems. The book builds on bachelor-level knowledge and is primarily intended for mathematicians and computer scientists, placing a strong emphasis on rigorous proofs. Prof. Dr. Dr. Stefan Schäffler, University of the German Federal Armed Forces Munich, Faculty of Electrical Engineering and Information Technology, Chair of Mathematics and Operations Research. The translation was done with the help of artificial intelligence. A subsequent human revision was done primarily in terms of content. This book is a translation of an original German edition. The translation was done with the help of artificial intelligence (machine translation by the service DeepL.com). A subsequent human revision was done primarily in terms of content, so that the book will read stylistically differently from a conventional translation. 410 0$aMathematics Study Resources,$x2731-3832 ;$v9 606 $aProbabilities 606 $aComputer science$xMathematics 606 $aQuantum computers 606 $aMathematical physics 606 $aStatistics 606 $aProbability Theory 606 $aMathematical Applications in Computer Science 606 $aQuantum Computing 606 $aMathematical Physics 606 $aStatistics 615 0$aProbabilities. 615 0$aComputer science$xMathematics. 615 0$aQuantum computers. 615 0$aMathematical physics. 615 0$aStatistics. 615 14$aProbability Theory. 615 24$aMathematical Applications in Computer Science. 615 24$aQuantum Computing. 615 24$aMathematical Physics. 615 24$aStatistics. 676 $a519.2 700 $aSchäffler$b Stefan$0768257 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 912 $a9910874667003321 996 $aMathematics of Information$94183650 997 $aUNINA