LEADER 02441nam 2200577 450 001 996202272803316 005 20230807214021.0 010 $a3-433-60593-9 010 $a3-433-60596-3 010 $a3-433-60594-7 035 $a(CKB)3710000000373797 035 $a(EBL)1987005 035 $a(SSID)ssj0001467473 035 $a(PQKBManifestationID)11865273 035 $a(PQKBTitleCode)TC0001467473 035 $a(PQKBWorkID)11517488 035 $a(PQKB)10722660 035 $a(MiAaPQ)EBC1987005 035 $a(EXLCZ)993710000000373797 100 $a20150323h20152015 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aAnalogous and digital /$fOtl Aicher ; with an introduction by Wilhelm Vossenkuhl 205 $a2nd ed. 210 1$a[Berlin, Germany] :$cErnst & Sohn,$d2015. 210 4$d©2015 215 $a1 online resource (189 p.) 300 $aDescription based upon print version of record. 311 $a3-433-03119-3 320 $aIncludes bibliographical references. 327 $aotl aicher analogous and digital; contents; preface by sir norman foster; Introduction; Authenticity and a questionable analogy; Knowing and making; Thinking and making; Critique of rationalism; Aicher today; grasping with the hand and mind; extensions of the ego; the eye, visual thinking; analogous and digital; afterword; universals and capitals; 1; 2; 3; 4; buridan and peirce; reading scores; honourable burial for descartes; design and philosophy; 1; 2; 3; 4; architecture and epistemology; use as philosophy; 1 wittgenstein as an architect; 2 haus wittgenstein; 3 we in the world; 4 use 327 $a5 school of making6 looking; appendix; planning and control; development, a concept; an apple; something quite ordinary; 1; 2; 3; life form and ideology; what is truth?; cultures of thinking; afterword; sources; End User License Agreement 606 $aArt$xPhilosophy 606 $aDesign$xPhilosophy 606 $aArchitecture$xPhilosophy 615 0$aArt$xPhilosophy. 615 0$aDesign$xPhilosophy. 615 0$aArchitecture$xPhilosophy. 676 $a741.6 700 $aAicher$b Otl$0502228 702 $aVossenkuhl$b Wilhelm$f1945- 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996202272803316 996 $aAnalogous and digital$92054502 997 $aUNISA LEADER 02930nam 2200625 450 001 9910788975903321 005 20230213215402.0 010 $a3-11-084185-1 024 7 $a10.1515/9783110841855 035 $a(CKB)3390000000033506 035 $a(EBL)3044881 035 $a(OCoLC)922948014 035 $a(SSID)ssj0001191688 035 $a(PQKBManifestationID)11695476 035 $a(PQKBTitleCode)TC0001191688 035 $a(PQKBWorkID)11217391 035 $a(PQKB)10278300 035 $a(MiAaPQ)EBC3044881 035 $a(DE-B1597)51620 035 $a(OCoLC)1013948662 035 $a(OCoLC)853247347 035 $a(DE-B1597)9783110841855 035 $a(Au-PeEL)EBL3044881 035 $a(CaPaEBR)ebr10802150 035 $a(EXLCZ)993390000000033506 100 $a20770210d1968 uy| 0 101 0 $ager 135 $aurnn#---|u||u 181 $ctxt 182 $cc 183 $acr 200 10$aAusgewa?hlte Schriften /$fErnst Kapp ; herausgegeben von Hans und Inez Diller 205 $aReprint 2013 210 1$aBerlin :$cWalter de Gruyter & Co.,$d1968. 215 $a1 online resource (337 p.) 225 1 $aUntersuchungen zur antiken Literatur und Geschichte 300 $aDescription based upon print version of record. 311 0 $a3-11-187026-X 311 0 $a3-11-005155-9 320 $aIncludes bibliographical references and indexes. 327 $tFront matter --$tInhalt --$tBesprechung: Wolfgang Schadewaldt, Die Geschichtschreibung des Thukydides. Ein Versuch. 1930 --$tBesprechung: Hermann Langerbeck, ???? ?????????. Studien zu Demokrits Ethik und Erkenntnislehre. 1936 --$t???????????. 1929 --$tThe Theory of Ideas in Plato's Earlier Dialogues. Nach 1942 --$tPlaton und die Akademie (Die Wissenschaft im Staat der Wirklichkeit). 1936 --$tTheorie und Praxis bei Aristoteles und Platon. 1938 --$tSokrates der Jüngere. 1924 --$tBesprechung: Hans von Arnim, Die drei aristotelischen Ethiken. 1927 --$tDie Kategorienlehre in der aristotelischen Topik. 1920 --$tSyllogistik. 1931 --$tCasus accusativus. 1956 --$tBesprechung: Philodemus, On Methods of Inference. A Study in Ancient Empiricism --$tDeum te scito esse? 1959 --$tBesprechung: Giorgio Pasquali, Preistoria della poesia romana. 1936 --$tBentley's Schediasma "De metris Terentianis" and the Modern Doctrine of Ictus in Classical Verse. 1941 --$tNachwort der Herausgeber --$tVerzeichnis der Schriften von Ernst Kapp --$tREGISTER --$tBackmatter 410 0$aUntersuchungen zur antiken Literatur und Geschichte 606 $aPhilosophy 615 0$aPhilosophy. 676 $a108 700 $aKapp$b Ernst$f1888-$0186718 701 $aDiller$b Hans$0185882 701 $aDiller$b Inez$0188168 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910788975903321 996 $aAusgewa?hlte Schriften$93866598 997 $aUNINA LEADER 05738nam 22006255 450 001 9910637722203321 005 20251202133759.0 010 $a3-031-13074-X 024 7 $a10.1007/978-3-031-13074-8 035 $a(MiAaPQ)EBC7166117 035 $a(Au-PeEL)EBL7166117 035 $a(CKB)25913966600041 035 $a(PPN)267816502 035 $a(OCoLC)1357017373 035 $a(DE-He213)978-3-031-13074-8 035 $a(EXLCZ)9925913966600041 100 $a20221223d2022 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aMachine Learning Applications in Electronic Design Automation /$fedited by Haoxing Ren, Jiang Hu 205 $a1st ed. 2022. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2022. 215 $a1 online resource (585 pages) 225 1 $aMathematics and Statistics Series 311 08$aPrint version: Ren, Haoxing Machine Learning Applications in Electronic Design Automation Cham : Springer International Publishing AG,c2023 9783031130731 320 $aIncludes bibliographical references and index. 327 $aIntroduction -- Analysis of Digital Design: Routability Optimization for Industrial Designs at Sub-14nm Process Nodes Using Machine Learning -- RouteNet: Routability Prediction for Mixed-size Designs Using Convolutional Neural Network -- High Performance Graph Convolutional networks with Applications in Testability Analysis -- MAVIREC: ML-Aided Vectored IR-Drop Estimation and Classification -- GRANNITE: Graph Neural Network Inference for Transferable Power Estimation -- Machine Learning-Enabled High-Frequency Low-Power Digital Design Implementation at Advanced Process Nodes -- Optimization of Digital Design: Chip Placement with Deep Reinforcement learning -- DREAMPlace: Deep Learning Toolkit-Enabled GPU Acceleration for Modern VLSI Placement -- TreeNet: Deep Point Cloud Embedding for Routing Tree Construction -- Asynchronous Reinforcement Learning Framework for Net Order Exploration in Detailed Routing -- Standard Cell Routing with Reinforcement Learning and Genetic Algorithm in Advanced Technology Nodes -- PrefixRL: Optimization of Parallel Prefix Circuits using Deep Reinforcement Learning -- GAN-CTS: A Generative Adversarial Framework for Clock Tree Prediction and Optimization -- Analysis and Optimization of Analog Design: Machine Learning Techniques in Analog Layout Automation -- Layout Symmetry Annotation for Analog Circuits with Graph Neural Networks -- ParaGraph: Layout parasitics and device parameter prediction using graph neural network -- GCN-RL circuit designer: Transferable transistor sizing with graph neural networks and reinforcement learn -- Parasitic-Aware Analog Circuit Sizing with Graph Neural Networks and Bayesian Optimization -- Logic and Physical Verification: Deep Predictive Coverage Collection/ Dynamically Optimized Test Generation Using Machine Learning -- Novelty-Driven Verification: Using Machine Learning to Identify Novel Stimuli and Close Coverage -- Using Machine Learning Clustering To Find Large Coverage Holes -- GAN-OPC: Mask optimization with lithography-guided generative adversarial nets -- Layout hotspot detection with feature tensor generation and deep biased learning. 330 $aThis book serves as a single-source reference to key machine learning (ML) applications and methods in digital and analog design and verification. Experts from academia and industry cover a wide range of the latest research on ML applications in electronic design automation (EDA), including analysis and optimization of digital design, analysis and optimization of analog design, as well as functional verification, FPGA and system level designs, design for manufacturing (DFM), and design space exploration. The authors also cover key ML methods such as classical ML, deep learning models such as convolutional neural networks (CNNs), graph neural networks (GNNs), generative adversarial networks (GANs) and optimization methods such as reinforcement learning (RL) and Bayesian optimization (BO). All of these topics are valuable to chip designers and EDA developers and researchers working in digital and analog designs and verification. Serves as a single-source reference to key machine learning (ML) applications and methods in digital and analog design and verification; Covers classical ML methods, as well as deep learning models such as convolutional neural networks (CNNs), graph neural networks (GNNs), generative adversarial networks (GANs) and optimization methods such as reinforcement learning (RL) and Bayesian optimization (BO); Discusses machine learning ML?s applications in electronic design automation (EDA), especially in the design automation of VLSI integrated circuits. 410 0$aMathematics and Statistics Series 606 $aElectronic circuits 606 $aEmbedded computer systems 606 $aElectronic circuit design 606 $aElectronic Circuits and Systems 606 $aEmbedded Systems 606 $aElectronics Design and Verification 615 0$aElectronic circuits. 615 0$aEmbedded computer systems. 615 0$aElectronic circuit design. 615 14$aElectronic Circuits and Systems. 615 24$aEmbedded Systems. 615 24$aElectronics Design and Verification. 676 $a929.374 676 $a621.38150285631 702 $aRen$b Haoxing 702 $aHu$b Jiang 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910637722203321 996 $aMachine learning applications in electronic design automation$93362878 997 $aUNINA