LEADER 02996nam a2200349Ii 4500 001 991003224319707536 008 070802s2001 enka s 001 0 eng d 020 $a9780750650892 020 $a0750650893 035 $ab13651328-39ule_inst 040 $aBibl. Dip.le Aggr. Ingegneria Innovazione - Sez. Ingegneria Innovazione$beng 082 04$a629.27$222 100 1 $aBonnick, Allan W. M.$0627335 245 10$aAutomotive computer controlled systems$h[e-book] :$bdiagnostic tools and techniques /$cAllan W.M. Bonnick 260 $aOxford ;$aBoston :$bButterworth-Heinemann,$c2001 300 $ax, 252 p. :$bill. ;$c25 cm 500 $aIncludes index 505 0 $aPreface; Common technology; The computer ECM; Self diagnosis and fault codes; Diagnostic tools and equipment; Sensors; Actuators; Diagnostic techniques; Additional technology; Appendices; Index 520 $a'Automotive Computer Controlled Systems' explains the fundamental principles of engineering that lie behind the operation of vehicle electronic systems. Having obtained this knowledge, the reader will be able to make full use of the diagnostic equipment which is currently available. The book builds on the concepts contained in Vehicle Electronic Systems and Fault Diagnosis and gives clear steps to fault diagnosis and subsequent repair of the vehicle's electronic systems. The author discusses electronics only within the context of the vehicle systems under consideration, and thus keeps theory to a minimum. Allan Bonnick has written articles for several transport/vehicle journals and carries out consultancy work for the Institute of Road Transport Engineers. In addition, he has had many years teaching experience and is ideally placed to write this informative guide. * Principles discussed in context avoiding unnecessary theory and maths * Practical step-by-step instructions on fault diagnosis and repair * Liberally illustrated with clear diagrams 533 $aElectronic reproduction.$bAmsterdam :$cElsevier Science & Technology,$d2007.$nMode of access: World Wide Web.$nSystem requirements: Web browser.$nTitle from title screen (viewed on July 25, 2007).$nAccess may be restricted to users at subscribing institutions 650 0$aAutomotive computers 650 0$aAutomobiles$xMaintenance and repair 655 7$aElectronic books.$2local 776 1 $cOriginal$z0750650893$z9780750650892$w(DLC) 2001018080$w(OCoLC)45756050 856 40$3Referex$uhttp://www.sciencedirect.com/science/book/9780750650892$zAn electronic book accessible through the World Wide Web; click for information 856 42$zPublisher description$uhttp://catdir.loc.gov/catdir/description/els031/2001018080.html 856 41$zTable of contents$uhttp://www.loc.gov/catdir/toc/els031/2001018080.html 907 $a.b13651328$b03-03-22$c24-01-08 912 $a991003224319707536 996 $aAutomotive computer controlled systems$91213355 997 $aUNISALENTO 998 $ale026$b24-01-08$cm$d@ $e-$feng$genk$h0$i0 LEADER 00877cam a2200241 a 4500 001 991003998779707536 008 030210s1995 uk 000 0 eng d 020 $a0631139214 035 $ab11895160-39ule_inst 040 $aDip.to Studi Storici$bita 082 $a411 100 1 $aWordhaugh, Rouald$0532662 245 10$aHow conversation works /$cRouald Wordhaugh 260 $aOxford ; New York :$bBlackwell in association with André Deutsch,$c1995 300 $a230 p. ;$c22 cm. 440 4$aThe language library 650 4$aConversazione 907 $a.b11895160$b02-04-14$c10-02-03 912 $a991003998779707536 945 $aLE023 411 WOR 1 1$g1$i2023000057612$lle023$nordini 2003 DUTI$o-$pE48.70$q-$rl$s- $t0$u0$v0$w0$x0$y.i12158823$z17-02-03 996 $aHow conversation works$9902065 997 $aUNISALENTO 998 $ale023$b10-02-03$cm$da $e-$feng$guk $h0$i1 LEADER 05009nam 22006975 450 001 9910349336003321 005 20200704182329.0 010 $a1-4471-7452-6 024 7 $a10.1007/978-1-4471-7452-3 035 $a(CKB)4100000009273666 035 $a(DE-He213)978-1-4471-7452-3 035 $a(MiAaPQ)EBC5918939 035 $a(PPN)269146105 035 $a(EXLCZ)994100000009273666 100 $a20190912d2019 u| 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aNeural Networks and Statistical Learning /$fby Ke-Lin Du, M. N. S. Swamy 205 $a2nd ed. 2019. 210 1$aLondon :$cSpringer London :$cImprint: Springer,$d2019. 215 $a1 online resource (XXX, 988 p. 184 illus., 70 illus. in color.) 311 $a1-4471-7451-8 327 $aIntroduction -- Fundamentals of Machine Learning -- Perceptrons -- Multilayer perceptrons: architecture and error backpropagation -- Multilayer perceptrons: other learing techniques -- Hopfield networks, simulated annealing and chaotic neural networks -- Associative memory networks -- Clustering I: Basic clustering models and algorithms -- Clustering II: topics in clustering -- Radial basis function networks -- Recurrent neural networks -- Principal component analysis -- Nonnegative matrix factorization and compressed sensing -- Independent component analysis -- Discriminant analysis -- Support vector machines -- Other kernel methods -- Reinforcement learning -- Probabilistic and Bayesian networks -- Combining multiple learners: data fusion and emsemble learning -- Introduction of fuzzy sets and logic -- Neurofuzzy systems -- Neural circuits -- Pattern recognition for biometrics and bioinformatics -- Data mining. 330 $aThis book provides a broad yet detailed introduction to neural networks and machine learning in a statistical framework. A single, comprehensive resource for study and further research, it explores the major popular neural network models and statistical learning approaches with examples and exercises and allows readers to gain a practical working understanding of the content. This updated new edition presents recently published results and includes six new chapters that correspond to the recent advances in computational learning theory, sparse coding, deep learning, big data and cloud computing. Each chapter features state-of-the-art descriptions and significant research findings. The topics covered include: ? multilayer perceptron; ? the Hopfield network; ? associative memory models; ? clustering models and algorithms; ? t he radial basis function network; ? recurrent neural networks; ? nonnegative matrix factorization; ? independent component analysis; ?probabilistic and Bayesian networks; and ? fuzzy sets and logic. Focusing on the prominent accomplishments and their practical aspects, this book provides academic and technical staff, as well as graduate students and researchers with a solid foundation and comprehensive reference on the fields of neural networks, pattern recognition, signal processing, and machine learning. 606 $aNeural networks (Computer science) 606 $aComputational intelligence 606 $aArtificial intelligence 606 $aPattern perception 606 $aSignal processing 606 $aImage processing 606 $aSpeech processing systems 606 $aMathematical Models of Cognitive Processes and Neural Networks$3https://scigraph.springernature.com/ontologies/product-market-codes/M13100 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 $aPattern Recognition$3https://scigraph.springernature.com/ontologies/product-market-codes/I2203X 606 $aSignal, Image and Speech Processing$3https://scigraph.springernature.com/ontologies/product-market-codes/T24051 615 0$aNeural networks (Computer science) 615 0$aComputational intelligence. 615 0$aArtificial intelligence. 615 0$aPattern perception. 615 0$aSignal processing. 615 0$aImage processing. 615 0$aSpeech processing systems. 615 14$aMathematical Models of Cognitive Processes and Neural Networks. 615 24$aComputational Intelligence. 615 24$aArtificial Intelligence. 615 24$aPattern Recognition. 615 24$aSignal, Image and Speech Processing. 676 $a001.534 700 $aDu$b Ke-Lin$4aut$4http://id.loc.gov/vocabulary/relators/aut$0756075 702 $aSwamy$b M. N. S$4aut$4http://id.loc.gov/vocabulary/relators/aut 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910349336003321 996 $aNeural Networks and Statistical Learning$92041918 997 $aUNINA