LEADER 00993nam0-2200325---450- 001 990004314790403321 005 20100622105752.0 010 $a0-7923-0651-1 035 $a000431479 035 $aFED01000431479 035 $a(Aleph)000431479FED01 035 $a000431479 100 $a19990604d1990----km-y0itay50------ba 101 0 $aeng 102 $aGB 105 $ay---a---001cy 200 1 $aHusserlian intentionality and non-foundational realism$enoema and object$fJohn J. Drummond 210 $aDordrecht ; Boston ; London$cKluwer Academic$dc 1990. 215 $aXII, 295 p.$d25 cm 225 1 $aContributions to phenomenology$v4 610 0 $aHusserl, Edmund 676 $a128.4 700 1$aDrummond,$bJohn J.$0171668 801 0$aIT$bUNINA$gREICAT$2UNIMARC 901 $aBK 912 $a990004314790403321 952 $aP.1 9D HUSS/S 65$bBiblio. 10446$fFLFBC 959 $aFLFBC 996 $aHusserlian intentionality and non-foundational realism$9488284 997 $aUNINA LEADER 04308nam 22006735 450 001 9910483610703321 005 20200703082358.0 010 $a3-319-90140-0 024 7 $a10.1007/978-3-319-90140-4 035 $a(CKB)3850000000035206 035 $a(DE-He213)978-3-319-90140-4 035 $a(MiAaPQ)EBC5921604 035 $a(PPN)227402421 035 $a(EXLCZ)993850000000035206 100 $a20180517d2019 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aModels of Neurons and Perceptrons: Selected Problems and Challenges /$fby Andrzej Bielecki 205 $a1st ed. 2019. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2019. 215 $a1 online resource (VI, 156 p. 30 illus.) 225 1 $aStudies in Computational Intelligence,$x1860-949X ;$v770 311 $a3-319-90139-7 320 $aIncludes bibliographical references. 327 $aIntroduction -- Part I: Preliminaries -- Foundations of arti?cial neural networks -- Part II: Mathematical foundations -- General foundations -- Foundations of dynamical systems theory -- Part III: Mathematical models of the neuron -- Models of the whole neuron -- Models of parts of the neuron -- Part IV: Mathematical models of the perceptron -- General model of the perceptron -- Linear perceptrons -- Weakly nonlinear perceptrons -- Nonlinear perceptrons -- Concluding remarks and comments. . 330 $aThis book describes models of the neuron and multilayer neural structures, with a particular focus on mathematical models. It also discusses electronic circuits used as models of the neuron and the synapse, and analyses the relations between the circuits and mathematical models in detail. The first part describes the biological foundations and provides a comprehensive overview of the artificial neural networks. The second part then presents mathematical foundations, reviewing elementary topics, as well as lesser-known problems such as topological conjugacy of dynamical systems and the shadowing property. The final two parts describe the models of the neuron, and the mathematical analysis of the properties of artificial multilayer neural networks. Combining biological, mathematical and electronic approaches, this multidisciplinary book it useful for the mathematicians interested in artificial neural networks and models of the neuron, for computer scientists interested in formal foundations of artificial neural networks, and for the biologists interested in mathematical and electronic models of neural structures and processes. 410 0$aStudies in Computational Intelligence,$x1860-949X ;$v770 606 $aComputational intelligence 606 $aArtificial intelligence 606 $aNeural networks (Computer science) 606 $aComputational complexity 606 $aNeurobiology 606 $aComputational Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/T11014 606 $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000 606 $aMathematical Models of Cognitive Processes and Neural Networks$3https://scigraph.springernature.com/ontologies/product-market-codes/M13100 606 $aComplexity$3https://scigraph.springernature.com/ontologies/product-market-codes/T11022 606 $aNeurobiology$3https://scigraph.springernature.com/ontologies/product-market-codes/L25066 615 0$aComputational intelligence. 615 0$aArtificial intelligence. 615 0$aNeural networks (Computer science) 615 0$aComputational complexity. 615 0$aNeurobiology. 615 14$aComputational Intelligence. 615 24$aArtificial Intelligence. 615 24$aMathematical Models of Cognitive Processes and Neural Networks. 615 24$aComplexity. 615 24$aNeurobiology. 676 $a591.188 700 $aBielecki$b Andrzej$4aut$4http://id.loc.gov/vocabulary/relators/aut$01225477 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910483610703321 996 $aModels of Neurons and Perceptrons: Selected Problems and Challenges$92845242 997 $aUNINA