LEADER 03674nam 2200697 450 001 9910816554103321 005 20230803200410.0 010 $a3-11-037535-4 010 $a3-11-039417-0 024 7 $a10.1515/9783110375350 035 $a(CKB)3360000000516321 035 $a(EBL)1727148 035 $a(SSID)ssj0001432517 035 $a(PQKBManifestationID)11778770 035 $a(PQKBTitleCode)TC0001432517 035 $a(PQKBWorkID)11405469 035 $a(PQKB)10376291 035 $a(MiAaPQ)EBC1727148 035 $a(DE-B1597)429455 035 $a(OCoLC)898769871 035 $a(OCoLC)906092445 035 $a(DE-B1597)9783110375350 035 $a(Au-PeEL)EBL1727148 035 $a(CaPaEBR)ebr11008754 035 $a(CaONFJC)MIL807957 035 $a(EXLCZ)993360000000516321 100 $a20150206h20142014 uy 0 101 0 $ager 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 14$aDas Paradigma deutscher Modalpartikeln $edialoggrammatische Funktion und paradigmeninterne Oppositionen /$fLena Bru?njes 210 1$aBerlin, [Germany] :$cWalter de Gruyter GmbH,$d2014. 210 4$d©2014 215 $a1 online resource (223 p.) 225 1 $aReihe Germanistische Linguistik,$x0344-6778 ;$v301 300 $aDescription based upon print version of record. 311 $a3-11-037529-X 320 $aIncludes bibliographical references. 327 $t Frontmatter -- $tInhalt -- $tAbbildungsverzeichnis -- $t1. Einleitung -- $t2. Forschungsbericht -- $t3. Paradigmatische Strukturiertheit als zentrales Merkmal grammatischer Zeichen -- $t4. Empirische Analyse: Bilden die Modalpartikeln ein grammatisches Paradigma? -- $t5. Rückblick und Ausblick -- $tLiteraturverzeichnis 330 $aDie Klassenfunktion der deutschen Modalpartikeln ist trotz einer 40-jährigen Forschungsgeschichte ungeklärt. Im Mittelpunkt der Debatte steht die Frage, ob die Partikeln eine grammatische Funktion oder rein pragmatische Funktionen besitzen. Diese Arbeit überprüft, ob die Modalpartikeln die zwei zentralen Kriterien für die Einordnung als grammatische Zeichen erfüllen: Besitzen alle Modalpartikeln eine relationale Funktion? Und: Bilden sie ein grammatisches Paradigma? Die Untersuchung dieser Fragen erfolgt auf Basis einer breit angelegten Korpusuntersuchung, in der alle zentralen Klassenmitglieder mit Hilfe zuvor entwickelter Paradigmatisierungstests analysiert werden.Die Ergebnisse der Untersuchung bestätigen nicht nur die These eines grammatischen Status der Modalpartikeln, sondern erlauben auch eine detaillierte Beschreibung des Modalpartikelparadigmas. Diese enthält sowohl differenzierte Angaben zur Distribution und Bedeutung einzelner Partikeln, als auch einen Vorschlag zur Erfassung der internen Struktur dieser Wortart. Darüberhinaus liefert die Arbeit neue Erkenntnisse zum Paradigmenbegriff und stellt Paradigmatisierungstests zur Verfügung, die auch auf andere grammatische Kaegorien anwendbar sind. 410 0$aReihe Germanistische Linguistik ;$v301. 606 $aGerman language$xParticles 606 $aGerman language$xModality 610 $aGrammaticalization. 610 $aModal Particles. 610 $aParadigms (Grammatical). 610 $aSemantic Analysis. 615 0$aGerman language$xParticles. 615 0$aGerman language$xModality. 676 $a35 686 $aGC 7117$2rvk 700 $aBru?njes$b Lena$01710162 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910816554103321 996 $aDas Paradigma deutscher Modalpartikeln$94100543 997 $aUNINA LEADER 03045nam 2200601Ia 450 001 9911020010403321 005 20230725025650.0 010 $a1-283-51427-3 010 $a9786613826725 010 $a1-4443-9056-2 010 $a1-4443-9054-6 035 $a(CKB)2670000000059111 035 $a(EBL)644966 035 $a(OCoLC)700706059 035 $a(SSID)ssj0000470939 035 $a(PQKBManifestationID)11312113 035 $a(PQKBTitleCode)TC0000470939 035 $a(PQKBWorkID)10413252 035 $a(PQKB)10326804 035 $a(MiAaPQ)EBC644966 035 $a(EXLCZ)992670000000059111 100 $a20100624d2010 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aLinguistic nativism and the poverty of the stimulus /$fAlex Clark and Shalom Lappin 210 $aMalden, MA $cWiley-Blackwell$d2010 215 $a1 online resource (262 p.) 300 $aDescription based upon print version of record. 311 $a1-4051-8784-0 320 $aIncludes bibliographical references and index. 327 $aLinguistic Nativism and the Poverty of the Stimulus; Contents; Preface; 1 Introduction: Nativism in Linguistic Theory; 2 Clarifying the Argument from the Poverty of the Stimulus; 3 The Stimulus: Determining the Nature of Primary Linguistic Data; 4 Learning in the Limit: The Gold Paradigm; 5 Probabilistic Learning Theory for Language Acquisition; 6 A Formal Model of Indirect Negative Evidence; 7 Computational Complexity and Efficient Learning; 8 Positive Results in Efficient Learning; 9 Grammar Induction through Implemented Machine Learning 327 $a10 Parameters in Linguistic Theory and Probabilistic Language Models11 A Brief Look at Some Biological and Psychological Evidence; 12 Conclusion; References; Author Index; Subject Index 330 $aThis unique contribution to the ongoing discussion of language acquisition considers the Argument from the Poverty of the Stimulus in language learning in the context of the wider debate over cognitive, computational, and linguistic issues. Critically examines the Argument from the Poverty of the Stimulus - the theory that the linguistic input which children receive is insufficient to explain the rich and rapid development of their knowledge of their first language(s) through general learning mechanismsFocuses on formal learnability properties of the class of natural languages, con 606 $aLanguage acquisition 606 $aNative language 606 $aComputational linguistics 615 0$aLanguage acquisition. 615 0$aNative language. 615 0$aComputational linguistics. 676 $a401.93 676 $a401/.93 700 $aClark$b Alexander$g(Alexander Simon)$01344741 701 $aLappin$b Shalom$0161732 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9911020010403321 996 $aLinguistic nativism and the poverty of the stimulus$94416093 997 $aUNINA LEADER 06156nam 22008055 450 001 9910484265303321 005 20251226202854.0 010 $a1-280-86452-4 010 $a9786610864522 010 $a3-540-70932-0 024 7 $a10.1007/978-3-540-70932-9 035 $a(CKB)1000000000284087 035 $a(SSID)ssj0000294429 035 $a(PQKBManifestationID)11265887 035 $a(PQKBTitleCode)TC0000294429 035 $a(PQKBWorkID)10312155 035 $a(PQKB)10949962 035 $a(DE-He213)978-3-540-70932-9 035 $a(MiAaPQ)EBC3036651 035 $a(MiAaPQ)EBC6283011 035 $a(PPN)123160332 035 $a(MiAaPQ)EBC302134 035 $a(EXLCZ)991000000000284087 100 $a20100301d2007 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt 182 $cc 183 $acr 200 10$aDynamical Vision $eICCV 2005 and ECCV 2006 Workshops, WDV 2005 and WDV 2006, Beijing, China, October 21, 2005, Graz, Austria, May 13, 2006, Revised Papers /$fedited by Rene Vidal, Anders Heyden, Yi Ma 205 $a1st ed. 2007. 210 1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d2007. 215 $a1 online resource (IX, 329 p.) 225 1 $aImage Processing, Computer Vision, Pattern Recognition, and Graphics,$x3004-9954 ;$v4358 300 $a"24 contributions presented at the First and Second International Workshops on Dynamical Vision, WDV 2006 and WDV 2006, which were held in conjunction with the 10th International Conference on Computer Vision (ICCV 2005) and 9th European Conference on Computer Vision (ECCV 2006), respectively"--Preface. 311 08$a3-540-70931-2 320 $aIncludes bibliographical references and index. 327 $aMotion Segmentation and Estimation -- The Space of Multibody Fundamental Matrices: Rank, Geometry and Projection -- Direct Segmentation of Multiple 2-D Motion Models of Different Types -- Motion Segmentation Using an Occlusion Detector -- Robust 3D Segmentation of Multiple Moving Objects Under Weak Perspective -- Nonparametric Estimation of Multiple Structures with Outliers -- Human Motion Analysis, Tracking and Recognition -- Articulated Motion Segmentation Using RANSAC with Priors -- Articulated-Body Tracking Through Anisotropic Edge Detection -- Homeomorphic Manifold Analysis: Learning Decomposable Generative Models for Human Motion Analysis -- View-Invariant Modeling and Recognition of Human Actions Using Grammars -- Dynamic Textures -- Segmenting Dynamic Textures with Ising Descriptors, ARX Models and Level Sets -- Spatial Segmentation of Temporal Texture Using Mixture Linear Models -- Online Video Registration of Dynamic Scenes Using Frame Prediction -- Dynamic Texture Recognition Using Volume Local Binary Patterns -- Motion Tracking -- A Rao-Blackwellized Parts-Constellation Tracker -- Bayesian Tracking with Auxiliary Discrete Processes. Application to Detection and Tracking of Objects with Occlusions -- Tracking of Multiple Objects Using Optical Flow Based Multiscale Elastic Matching -- Real-Time Tracking with Classifiers -- Rigid and Non-rigid Motion Analysis -- A Probabilistic Framework for Correspondence and Egomotion -- Estimating the Pose of a 3D Sensor in a Non-rigid Environment -- A Batch Algorithm for Implicit Non-rigid Shape and Motion Recovery -- Motion Filtering and Vision-Based Control -- Using a Connected Filter for Structure Estimation in Perspective Systems -- Recursive Structure from Motion Using Hybrid Matching Constraints with Error Feedback -- Force/Vision Based Active Damping Control of Contact Transition in Dynamic Environments -- Segmentation and Guidance of Multiple Rigid Objects for Intra-operative Endoscopic Vision. 330 $aClassical multiple-view geometry studies the reconstruction of a static scene - served by a rigidly moving camera. However, in many real-world applications the scene may undergo much more complex dynamical changes. For instance, the scene may consist of multiple moving objects (e.g., a tra?c scene) or arti- lated motions (e.g., a walking human) or even non-rigid dynamics (e.g., smoke, ?re, or a waterfall). In addition, some applications may require interaction with the scene through a dynamical system (e.g., vision-guided robot navigation and coordination). To study the problem of reconstructing dynamical scenes, many new al- braic, geometric, statistical, and computational tools have recently emerged in computer vision, computer graphics, image processing, and vision-based c- trol. The goal of the International Workshop on Dynamical Vision (WDV) is to converge di?erent aspects of the research on dynamical vision and to identify common mathematical problems, models, and methods for future research in this emerging and active area. 410 0$aImage Processing, Computer Vision, Pattern Recognition, and Graphics,$x3004-9954 ;$v4358 606 $aComputer vision 606 $aPattern recognition systems 606 $aComputer graphics 606 $aUser interfaces (Computer systems) 606 $aHuman-computer interaction 606 $aComputer Vision 606 $aAutomated Pattern Recognition 606 $aComputer Graphics 606 $aUser Interfaces and Human Computer Interaction 615 0$aComputer vision. 615 0$aPattern recognition systems. 615 0$aComputer graphics. 615 0$aUser interfaces (Computer systems) 615 0$aHuman-computer interaction. 615 14$aComputer Vision. 615 24$aAutomated Pattern Recognition. 615 24$aComputer Graphics. 615 24$aUser Interfaces and Human Computer Interaction. 676 $a006.37 702 $aVidal$b Rene?$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aHeyden$b Anders$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aMa$b Yi$4edt$4http://id.loc.gov/vocabulary/relators/edt 712 12$aWDV 2006$f(2006 :$eGraz, Austria) 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910484265303321 996 $aDynamical Vision$9772521 997 $aUNINA