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Introduction to S-systems and the underlying power-law formalism

dc.contributor.authorSavageau, Michael A.en_US
dc.date.accessioned2006-04-07T20:32:53Z
dc.date.available2006-04-07T20:32:53Z
dc.date.issued1988en_US
dc.identifier.citationSavageau, Michael A. (1988)."Introduction to S-systems and the underlying power-law formalism." Mathematical and Computer Modelling 11(): 546-551. <http://hdl.handle.net/2027.42/27576>en_US
dc.identifier.urihttp://www.sciencedirect.com/science/article/B6V0V-45GVR9V-8V/2/cf303b4382e167258484a655046a3845en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/27576
dc.description.abstractA novel approach to the development of an appropriate formalism for representing organizationally complex systems began in the mid 1960's with a search for a general systematic formalism that would retain the essential nonlinear features and that would still be amenable to mathematical analysis. The set of nonlinear differential equations that most closely approached this goal was called an "S-system", because it accurately captures the saturable and synergistic properties intrinsic to biological and other organizationally complex systems. In the early 1980's it was found that essentially any nonlinear differential equation composed of elementary functions could be recast exactly as an S-system. Thus, S-systems may be considered a canonical form with the ability to represent an enormous variety of nonlinear differential equations. This has given rise to new strategies for the mathematical modeling of nonlinear systems.en_US
dc.format.extent721562 bytes
dc.format.extent3118 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypetext/plain
dc.language.isoen_US
dc.publisherElsevieren_US
dc.titleIntroduction to S-systems and the underlying power-law formalismen_US
dc.typeArticleen_US
dc.rights.robotsIndexNoFollowen_US
dc.subject.hlbsecondlevelPhilosophyen_US
dc.subject.hlbsecondlevelComputer Scienceen_US
dc.subject.hlbtoplevelHumanitiesen_US
dc.subject.hlbtoplevelEngineeringen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumDepartment of Microbiology and Immunology, The University of Michigan, Ann Arbor, Michigan 48109 USAen_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/27576/1/0000620.pdfen_US
dc.identifier.doihttp://dx.doi.org/10.1016/0895-7177(88)90553-5en_US
dc.identifier.sourceMathematical and Computer Modellingen_US
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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