04101 am 2200673 n 450 9910131373803321201504162-11-139837-3(CKB)3710000000491152(FrMaCLE)OB-deps-787(oapen)https://directory.doabooks.org/handle/20.500.12854/45115(EXLCZ)99371000000049115220150921j|||||||| ||| 0freuu||||||m||||txtrdacontentcrdamediacrrdacarrierDiffusion et utilisation des TIC en France et en Europe /Pierre BerretParis Département des études, de la prospective et des statistiques20151 online resource (16 p.) L’exploitation par le DEPS des enquêtes communautaires sur l’utilisation des TIC par les ménages et les particuliers, coordonnées, harmonisées et publiées par Eurostat, permet de dresser un portrait comparatif et en tendances de l’équipement en TIC, des modes d’accès à l’internet des ménages dans l’UE- 27 selon leurs caractéristiques socio-démographiques. Elle met en lumière l’intensification des usages numériques des particuliers, élucide les facteurs de développement des TIC que sont les usages culturels et le commerce électronique de produits culturels, mais aussi la forte liaison entre accès aux TIC et commerce électronique dans l’Union européenne. Enfin, sont établis des tendances et facteurs d’usages convergents sur l’internet, la télévision et la téléphonie: disponibilité, temps d’usages, générations, praticité, etc. Dans cette cartographie de l’accès et de l’utilisation des TIC dans l’UE, la France occupe une position intermédiaire: plutôt en dessous de la moyenne de l’UE en termes d’accès ou de téléphonie mobile, elle est plutôt au-dessus de cette moyenne en termes d’usages et de commerce électronique. The analysis by the DEPS of the Community surveys, coordinated, harmonised and published by Eurostat, on households’ and individuals’ ICT use offers a comparative picture of and reveals trends in ICT equipment and Internet access patterns in EU-27 households according to their socio-demogra- phic characteristics. It casts light on the stepped-up digital practices of individuals, while explaining the factors behind ICT development, such as cultural habits, electronic trade in cultural products and the close connection between ICT access and electronic trade in the European Union. Proof is given of converging trends and factors governing Internet, television and telephone use – such as availability, time spent, generation, degree of practice. In this topography of ICT access and use in the EU, France occupies an in-between place. Whereas it ranks somewhat…SociologyINSEEéquipement culturelTICconsommation des ménagesinternetnumériquehouseholds expenditurecultural institutionINSEE (National Institute of statistics and economic studies)digitalICTdigitalINSEE (National Institute of statistics and economic studies)households expenditureICTcultural institutioninternetSociologyINSEEéquipement culturelTICconsommation des ménagesinternetnumériquehouseholds expenditurecultural institutionINSEE (National Institute of statistics and economic studies)digitalICTBerret Pierre1319148Chantepie Philippe1281727FR-FrMaCLEBOOK9910131373803321Diffusion et utilisation des TIC en France et en Europe3033643UNINA05475nam 2200649 a 450 991081872850332120230803023846.01-118-65097-21-118-65098-01-118-65096-4(CKB)2560000000103656(EBL)1213812(OCoLC)851316215(DLC) 2013018480(OCoLC)842337745(MiAaPQ)EBC1213812(Au-PeEL)EBL1213812(CaPaEBR)ebr10719141(CaONFJC)MIL497783(EXLCZ)99256000000010365620150303d2013 uy 0engur|n|---|||||rdacontentrdamediardacarrierFiltering, control, and fault detection with randomly occurring incomplete information /Hongli Dong, Zidong Wang, Huijun Gao1st ed.Chichester, West Sussex, U.K. Wileyc20131 online resource (283 p.)Description based upon print version of record.1-118-64791-2 Includes bibliographical references and index.FILTERING, CONTROL AND FAULT DETECTION WITH RANDOMLY OCCURRING INCOMPLETE INFORMATION; Contents; Preface; Acknowledgments; List of Abbreviations; List of Notations; 1 Introduction; 1.1 Background, Motivations, and Research Problems; 1.1.1 Randomly Occurring Incomplete Information; 1.1.2 The Analysis and Synthesis of Nonlinear Stochastic Systems; 1.1.3 Distributed Filtering over Sensor Networks; 1.2 Outline; 2 Variance-Constrained Finite-Horizon Filtering and Control with Saturations; 2.1 Problem Formulation for Finite-Horizon Filter Design; 2.2 Analysis of H and Covariance Performances2.2.1 H Performance2.2.2 Variance Analysis; 2.3 Robust Finite-Horizon Filter Design; 2.4 Robust H Finite-Horizon Control with Sensor and Actuator Saturations; 2.4.1 Problem Formulation; 2.4.2 Main Results; 2.5 Illustrative Examples; 2.5.1 Example 1; 2.5.2 Example 2; 2.6 Summary; 3 Filtering and Control with Stochastic Delays and Missing Measurements; 3.1 Problem Formulation for Robust Filter Design; 3.2 Robust H Filtering Performance Analysis; 3.3 Robust H Filter Design; 3.4 Robust H Fuzzy Control; 3.4.1 Problem Formulation; 3.4.2 Performance Analysis; 3.4.3 Controller Design3.5 Illustrative Examples3.5.1 Example 1; 3.5.2 Example 2; 3.5.3 Example 3; 3.6 Summary; 4 Filtering and Control for Systems with Repeated Scalar Nonlinearities; 4.1 Problem Formulation for Filter Design; 4.1.1 The Physical Plant; 4.1.2 The Communication Link; 4.1.3 The Filter; 4.1.4 The Filtering Error Dynamics; 4.2 Filtering Performance Analysis; 4.3 Filter Design; 4.4 Observer-Based H Control with Multiple Packet Losses; 4.4.1 Problem Formulation; 4.4.2 Main Results; 4.5 Illustrative Examples; 4.5.1 Example 1; 4.5.2 Example 2; 4.5.3 Example 3; 4.5.4 Example 4; 4.6 Summary5 Filtering and Fault Detection for Markov Systems with Varying Nonlinearities5.1 Problem Formulation for Robust H° Filter Design; 5.2 Performance Analysis of Robust H° Filter; 5.3 Design of Robust H° Filters; 5.4 Fault Detection with Sensor Saturations and Randomly Varying Nonlinearities; 5.4.1 Problem Formulation; 5.4.2 Main Results; 5.5 Illustrative Examples; 5.5.1 Example 1; 5.5.2 Example 2; 5.5.3 Example 3; 5.5.4 Example 4; 5.6 Summary; 6 Quantized Fault Detection with Mixed Time-Delays and Packet Dropouts; 6.1 Problem Formulation for Fault Detection Filter Design; 6.2 Main Results6.3 Fuzzy-Model-Based Robust Fault Detection6.3.1 Problem Formulation; 6.3.2 Main Results; 6.4 Illustrative Examples; 6.4.1 Example 1; 6.4.2 Example 2; 6.5 Summary; 7 Distributed Filtering over Sensor Networks with Saturations; 7.1 Problem Formulation; 7.2 Main Results; 7.3 An Illustrative Example; 7.4 Summary; 8 Distributed Filtering with Quantization Errors: The Finite-Horizon Case; 8.1 Problem Formulation; 8.2 Main Results; 8.3 An Illustrative Example; 8.4 Summary; 9 Distributed Filtering for Markov Jump Nonlinear Time-Delay Systems; 9.1 Problem Formulation9.1.1 Deficient Statistics of Markovian Modes Transitions In the context of systems and control, incomplete information refers to a dynamical system in which knowledge about the system states is limited due to the difficulties in modelling complexity in a quantitative way. The well-known types of incomplete information include parameter uncertainties and norm-bounded nonlinearities. Recently, in response to the development of network technologies, the phenomenon of randomly occurring incomplete information has become more and more prevalent. Filtering, Control and Fault Detection with Randomly Occurring Incomplete Information reflectsAutomatic controlElectric filters, DigitalFault tolerance (Engineering)Automatic control.Electric filters, Digital.Fault tolerance (Engineering)629.83202855369Dong Hongli1977-1635787Wang Zidong1966-1635788Gao Huijun739791MiAaPQMiAaPQMiAaPQBOOK9910818728503321Filtering, control, and fault detection with randomly occurring incomplete information3976750UNINA