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001 978-3-319-26630-5
003 DE-He213
005 20200421111156.0
007 cr nn 008mamaa
008 160128s2016 gw | s |||| 0|eng d
020 _a9783319266305
_9978-3-319-26630-5
024 7 _a10.1007/978-3-319-26630-5
_2doi
050 4 _aQA76.9.M35
072 7 _aGPFC
_2bicssc
072 7 _aTEC000000
_2bisacsh
082 0 4 _a620
_223
245 1 0 _aMathematical Modeling and Applications in Nonlinear Dynamics
_h[electronic resource] /
_cedited by Albert C.J. Luo, H�useyin Merdan.
250 _a1st ed. 2016.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2016.
300 _aVII, 205 p. 31 illus., 1 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aNonlinear Systems and Complexity,
_x2195-9994 ;
_v14
505 0 _aFrom the Contents: Introduction -- Mathematical Neuroscience: from neurons to networks -- Jupiters belts, our Ozone holes, and Degenerate tori -- Analytical solutions of periodic motions in time-delay systems -- DNA elasticity and its biological implications -- Epidemiology, dynamics, control and multi-patch mobility.
520 _aThe book covers nonlinear physical problems and mathematical modeling, including molecular biology, genetics, neurosciences, artificial intelligence with classical problems in mechanics and astronomy and physics. The chapters present nonlinear mathematical modeling in life science and physics through nonlinear differential equations, nonlinear discrete equations and hybrid equations. Such modeling can be effectively applied to the wide spectrum of nonlinear physical problems, including the KAM (Kolmogorov-Arnold-Moser (KAM)) theory, singular differential equations, impulsive dichotomous linear systems, analytical bifurcation trees of periodic motions, and almost or pseudo- almost periodic solutions in nonlinear dynamical systems. Provides methods for mathematical models with switching, thresholds, and impulses, each of particular importance for discontinuous processes Includes qualitative analysis of behaviors on Tumor-Immune Systems and methods of analysis for DNA, neural networks and epidemiology Introduces new concepts, methods, and applications in nonlinear dynamical systems covering physical problems and mathematical modeling relevant to molecular biology, genetics, neurosciences, artificial intelligence as well as classic problems in mechanics, astronomy, and physics Demonstrates mathematic modeling relevant to molecular biology, genetics, neurosciences, artificial intelligence as well as classic problems in mechanics, astronomy, and physics.
650 0 _aEngineering.
650 0 _aSystems biology.
650 0 _aNeural networks (Computer science).
650 0 _aPhysics.
650 0 _aStatistical physics.
650 0 _aComplexity, Computational.
650 1 4 _aEngineering.
650 2 4 _aComplexity.
650 2 4 _aMathematical Models of Cognitive Processes and Neural Networks.
650 2 4 _aNonlinear Dynamics.
650 2 4 _aSystems Biology.
650 2 4 _aComplex Networks.
700 1 _aLuo, Albert C.J.
_eeditor.
700 1 _aMerdan, H�useyin.
_eeditor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783319266282
830 0 _aNonlinear Systems and Complexity,
_x2195-9994 ;
_v14
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-319-26630-5
912 _aZDB-2-ENG
942 _cEBK
999 _c53501
_d53501