LEADER 03667nam 2200805 450 001 9910790832503321 005 20230803220638.0 010 $a3-11-026828-0 024 7 $a10.1515/9783110268287 035 $a(CKB)2550000001169782 035 $a(EBL)1130390 035 $a(OCoLC)865329972 035 $a(SSID)ssj0001060764 035 $a(PQKBManifestationID)11985606 035 $a(PQKBTitleCode)TC0001060764 035 $a(PQKBWorkID)11087638 035 $a(PQKB)10627849 035 $a(MiAaPQ)EBC1130390 035 $a(DE-B1597)173647 035 $a(OCoLC)955604655 035 $a(OCoLC)979906368 035 $a(DE-B1597)9783110268287 035 $a(Au-PeEL)EBL1130390 035 $a(CaPaEBR)ebr10819967 035 $a(CaONFJC)MIL551767 035 $a(EXLCZ)992550000001169782 100 $a20130612h20142014 uy| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aComplexity and evolution of dissipative systems $ean analytical approach /$fSergey Vakulenko 210 1$aBerlin ;$aBoston :$cWalter de Gruyter GmbH & Co., KG,$d[2014] 210 4$dİ2014 215 $a1 online resource (316 p.) 225 0 $aDe Gruyter Series in Mathematics and Life Sciences ;$v4 225 0$aDe Gruyter series in mathematics and life sciences,$x2195-5530 ;$v4 300 $aDescription based upon print version of record. 311 $a3-11-026648-2 311 $a1-306-20516-6 320 $aIncludes bibliographical references and index. 327 $t Frontmatter -- $tPreface -- $tContents -- $t1. Introduction -- $t2. Complex dynamics in neural and genetic networks -- $t3. Complex patterns and attractors for reaction-diffusion systems -- $t4. Random perturbations, evolution and complexity -- $tBibliography -- $tIndex -- $t Backmatter 330 $aThis book focuses on the dynamic complexity of neural, genetic networks, and reaction diffusion systems. The author shows that all robust attractors can be realized in dynamics of such systems. In particular, a positive solution of the Ruelle-Takens hypothesis for on chaos existence for large class of reaction-diffusion systems is given. The book considers viability problems for such systems - viability under extreme random perturbations - and discusses an interesting hypothesis of M. Gromov and A. Carbone on biological evolution. There appears a connection with the Kolmogorov complexity theory. As applications, transcription-factors-microRNA networks are considered, patterning in biology, a new approach to estimate the computational power of neural and genetic networks, social and economical networks, and a connection with the hard combinatorial problems. 410 3$aDe Gruyter Series in Mathematics and Life Sciences 606 $aMathematical physics 606 $aEnergy dissipation 606 $aBiophysics 606 $aAttractors (Mathematics) 606 $aChaotic behavior in systems 610 $aBiological Evolution. 610 $aDynamic Network Complexity. 610 $aFluid Dynamic Equation. 610 $aReaction Diffusion System. 610 $aViability Problem. 615 0$aMathematical physics. 615 0$aEnergy dissipation. 615 0$aBiophysics. 615 0$aAttractors (Mathematics) 615 0$aChaotic behavior in systems. 676 $a003 686 $aSK 560$2rvk 700 $aVakulenko$b Sergey$01567186 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910790832503321 996 $aComplexity and evolution of dissipative systems$93838403 997 $aUNINA