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001 978-3-319-62063-3
003 DE-He213
005 20210201191533.0
007 cr nn 008mamaa
008 170816s2018 gw | s |||| 0|eng d
020 _a9783319620633
_9978-3-319-62063-3
050 4 _aTK1-9971
072 7 _aTHR
_2bicssc
072 7 _aTEC007000
_2bisacsh
072 7 _aTHR
_2thema
082 0 4 _a621.3
_223
100 1 _aMerhav, Neri.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
245 1 0 _aStatistical Physics for Electrical Engineering
_h[electronic resource] /
_cby Neri Merhav.
250 _a1st ed. 2018.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2018.
300 _aXII, 137 p. 21 illus., 3 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
500 _aAcceso multiusuario
505 0 _aPreface -- Introduction -- Kinetic Theory and the Maxwell Distribution -- Elementary Statistical Physics -- Quantum Statistics - the Fermi-Dirac Distribution -- Quantum Statistics - the Bose-Einstein Distribution -- Interacting Particle Systems and Phase Transitions -- Vibrations in a Solid - Phonons and Heat Capacity -- Fluctuations, Stochastic Dynamics and Noise -- A Brief Touch on Information Theory.
520 _aThe main body of this book is devoted to statistical physics, whereas much less emphasis is given to thermodynamics. In particular, the idea is to present the most important outcomes of thermodynamics - most notably, the laws of thermodynamics - as conclusions from derivations in statistical physics. Special emphasis is on subjects that are vital to engineering education. These include, first of all, quantum statistics, like the Fermi-Dirac distribution, as well as diffusion processes, both of which are fundamental to a sound understanding of semiconductor devices. Another important issue for electrical engineering students is understanding of the mechanisms of noise generation and stochastic dynamics in physical systems, most notably in electric circuitry. Accordingly, the fluctuation-dissipation theorem of statistical mechanics, which is the theoretical basis for understanding thermal noise processes in systems, is presented from a signals-and-systems point of view, in a way that is readily accessible for engineering students and in relation with other courses in the electrical engineering curriculum, like courses on random processes.
541 _fUABC ;
_cTemporal ;
_d01/01/2021-12/31/2023.
650 0 _aElectrical engineering.
650 0 _aStatistical physics.
650 0 _aStatistics .
650 0 _aPhysics.
650 0 _aMathematical physics.
650 1 4 _aElectrical Engineering.
_0https://scigraph.springernature.com/ontologies/product-market-codes/T24000
650 2 4 _aStatistical Physics and Dynamical Systems.
_0https://scigraph.springernature.com/ontologies/product-market-codes/P19090
650 2 4 _aStatistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences.
_0https://scigraph.springernature.com/ontologies/product-market-codes/S17020
650 2 4 _aMathematical Methods in Physics.
_0https://scigraph.springernature.com/ontologies/product-market-codes/P19013
650 2 4 _aMathematical Physics.
_0https://scigraph.springernature.com/ontologies/product-market-codes/M35000
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783319620626
776 0 8 _iPrinted edition:
_z9783319620640
776 0 8 _iPrinted edition:
_z9783319872247
856 4 0 _zLibro electrónico
_uhttp://148.231.10.114:2048/login?url=https://doi.org/10.1007/978-3-319-62063-3
912 _aZDB-2-ENG
912 _aZDB-2-SXE
942 _cLIBRO_ELEC
999 _c244608
_d244607