LEADER 03989nam  22007215  450 
001 9910151857903321
005 20200701140747.0
010   $a3-319-43222-2
024 7 $a10.1007/978-3-319-43222-9
035   $a(CKB)3710000000952899
035   $a(DE-He213)978-3-319-43222-9
035   $a(MiAaPQ)EBC4743985
035   $a(PPN)197140637
035   $a(EXLCZ)993710000000952899
100   $a20161115d2016      u|         0
101 0 $aeng
135   $aurnn|008mamaa
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 13$aAn Introduction to Transfer Entropy $eInformation Flow in Complex Systems /$fby Terry Bossomaier, Lionel Barnett, Michael Harré, Joseph T. Lizier
205   $a1st ed. 2016.
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2016.
215   $a1 online resource (XXIX, 190 p. 24 illus., 21 illus. in color.) 
311   $a3-319-43221-4 
320   $aIncludes bibliographical references and index.
327   $aIntroduction -- Statistical Preliminaries -- Information Theory -- Transfer Entropy -- Information Transfer in Canonical Systems -- Information Transfer in Financial Markets -- Miscellaneous Applications of Transfer Entropy -- Concluding Remarks.
330   $aThis book considers a relatively new metric in complex systems, transfer entropy, derived from a series of measurements, usually a time series. After a qualitative introduction and a chapter that explains the key ideas from statistics required to understand the text, the authors then present information theory and transfer entropy in depth. A key feature of the approach is the authors' work to show the relationship between information flow and complexity. The later chapters demonstrate information transfer in canonical systems, and applications, for example in neuroscience and in finance. The book will be of value to advanced undergraduate and graduate students and researchers in the areas of computer science, neuroscience, physics, and engineering.
606   $aArtificial intelligence
606   $aApplied mathematics
606   $aEngineering mathematics
606   $aStatistical physics
606   $aDynamical systems
606   $aNeurosciences
606   $aComputers
606   $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000
606   $aMathematical and Computational Engineering$3https://scigraph.springernature.com/ontologies/product-market-codes/T11006
606   $aComplex Systems$3https://scigraph.springernature.com/ontologies/product-market-codes/P33000
606   $aNeurosciences$3https://scigraph.springernature.com/ontologies/product-market-codes/B18006
606   $aTheory of Computation$3https://scigraph.springernature.com/ontologies/product-market-codes/I16005
606   $aStatistical Physics and Dynamical Systems$3https://scigraph.springernature.com/ontologies/product-market-codes/P19090
615  0$aArtificial intelligence.
615  0$aApplied mathematics.
615  0$aEngineering mathematics.
615  0$aStatistical physics.
615  0$aDynamical systems.
615  0$aNeurosciences.
615  0$aComputers.
615 14$aArtificial Intelligence.
615 24$aMathematical and Computational Engineering.
615 24$aComplex Systems.
615 24$aNeurosciences.
615 24$aTheory of Computation.
615 24$aStatistical Physics and Dynamical Systems.
676   $a006.3
700   $aBossomaier$b Terry$4aut$4http://id.loc.gov/vocabulary/relators/aut$062672
702   $aBarnett$b Lionel$4aut$4http://id.loc.gov/vocabulary/relators/aut
702   $aHarré$b Michael$4aut$4http://id.loc.gov/vocabulary/relators/aut
702   $aLizier$b Joseph T$4aut$4http://id.loc.gov/vocabulary/relators/aut
906   $aBOOK
912   $a9910151857903321
996   $aAn Introduction to Transfer Entropy$92214300
997   $aUNINA