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[null,"1.","Record Nr.",null,"UNINA9910824636703321"]
[null,null,"Autore",null,"Minoli Daniel <1952->"]
[null,null,"Titolo",null,"IP multicast with applications to IPTV and mobile DVB-H / / Daniel Minoli"]
[null,null,"Pubbl/distr/stampa",null,"Hoboken, N.J., : Wiley-Interscience, c2008"]
[null,null,"ISBN",null,"9786611284817"]
[{"$nulls":4},"9780470653029"]
[{"$nulls":4},"0470653027"]
[{"$nulls":4},"9781281284815"]
[{"$nulls":4},"1281284815"]
[{"$nulls":4},"9780470260876"]
[{"$nulls":4},"0470260874"]
[{"$nulls":4},"9780470260869"]
[{"$nulls":4},"0470260866"]
[null,null,"Edizione",null,"[1st ed.]"]
[null,null,"Descrizione fisica",null,"1 online resource (375 p.)"]
[null,null,"Disciplina",null,"004.66"]
[{"$nulls":4},"006.7"]
[null,null,"Soggetti",null,"Digital video"]
[{"$nulls":4},"Internet television"]
[{"$nulls":4},"Webcasting"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Description based upon print version of record."]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and index."]
[null,null,"Nota di contenuto",null,"Preface -- About the Author -- 1 INTRODUCTION TO IP MULTICAST -- 1.1 Introduction -- 1.2 Why Multicast Protocols are Wanted/Needed -- 1.3 Basic Multicast Protocols and Concepts -- 1.4 IPTV and DVB-H Applications -- 1.5 Course of Investigation -- Appendix 1.A: Multicast IETF Request for Comments -- Appendix 1.B: Multicast Bibliography -- 2 MULTICAST ADDRESSING FOR PAYLOAD -- 2.1 IP Multicast Addresses -- 2.2 Layer 2 Multicast Addresses -- 2.2.1 Ethernet MAC Address Mapping -- 2.3 MPEG-Layer Addresses -- 3 MULTICAST PAYLOAD FORWARDING -- 3.1 Multicasting on a LAN Segment -- 3.2 Multicasting between Network Segments -- 3.3 Multicast Distribution Trees -- 3.4 Multicast Forwarding: Reverse Path Forwarding -- 3.5 Multicast Forwarding: Center-Based Tree Algorithm -- 3.6 Implementing IP Multicast in a Network -- 4 DYNAMIC HOST REGISTRATION--INTERNET GROUP MANAGEMENT PROTOCOL -- 4.1 "]
[{"$nulls":4},"IGMP Messages -- 4.2 IGMPv3 Messages -- 4.3 IGMP Operation -- Appendix 4.A: Protocol Details for IGMPv2 -- Appendix 4.B: IGMP Snooping Switches -- Appendix 4.C: Example of Router Configurations -- 5 MULTICAST ROUTING--SPARSE-MODE PROTOCOLS: PROTOCOL INDEPENDENT MULTICAST -- 5.1 Introduction to PIM -- 5.2 PIM SM Details -- 6 MULTICAST ROUTING--SPARSE-MODE PROTOCOLS: CORE-BASED TREES -- 6.1 Motivation 126 -- 6.2 Basic Operation -- 6.3 CBT Components and Functions -- 6.4 Core Router Discovery -- 6.5 Protocol Specification Details -- 6.6 CBT Version 3 -- 7 MULTICAST ROUTING--DENSE-MODE PROTOCOLS: PIM DM -- 7.1 Overview -- 7.2 Basic PIM DM Behavior -- 7.3 Protocol Specification -- 8 OTHER DENSE-MODE MULTICAST ROUTING PROTOCOLS: DVMRP AND MOSPF -- 8.1 Distance Vector Multicast Algorithm -- 8.2 Multicast OSPF -- 9 IP MULTICASTING IN IPv6 ENVIRONMENTS -- 9.1 Opportunities Offered by IPv6 -- 9.2 Introductory Overview of IPv6 -- 9.3 Migration and Coexistence -- 9.4 Multicast with IPv6 -- 10 MULTICAST LISTENER DISCOVERY -- 10.1 Overview of MLDv1 -- 10.2 Message Format."]
[{"$nulls":4},"10.3 Protocol Description -- 10.4 Node State Transition Diagram -- 10.5 Router State Transition Diagram -- 10.6 Overview of MLDv2 -- 10.7 Source Filtering -- 11 IPTV APPLICATIONS -- 11.1 Overview and Motivation -- 11.2 Basic Architecture -- Appendix 11.A: Serial Digital Interface Basics -- Appendix 11.B: MPEG Basics -- Appendix 11.C: Encapsulation for Transmission of IP Datagrams over MPEG-2/DVB Networks -- 12 DVB-H: HIGH-QUALITY TV TO CELL PHONES -- 12.1 Background and Motivation -- 12.2 Basic DVB-H Technology -- Appendix 12.A: Open Mobile Video Coalition Efforts -- References -- Glossary -- Index."]
[null,null,null,"Sommario/riassunto","Get a clear picture of IP Multicast applications for delivering commercial high-quality video services. This book provides a concise guide to current IP Multicast technology and its applications, with a focus on IP-based Television (IPTV) and Dig."]
[null,"2.","Record Nr.",null,"UNINA9911021962903321"]
[null,null,"Autore",null,"Calder Jeff"]
[null,null,"Titolo",null,"Linear Algebra, Data Science, and Machine Learning / / by Jeff Calder, Peter J. Olver"]
[null,null,"Pubbl/distr/stampa",null,"Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025"]
[null,null,"ISBN",null,"9783031937644"]
[{"$nulls":4},"9783031937637"]
[null,null,"Edizione",null,"[1st ed. 2025.]"]
[null,null,"Descrizione fisica",null,"1 online resource (645 pages)"]
[null,null,"Collana",null,"Springer Undergraduate Texts in Mathematics and Technology, , 1867-5514"]
[null,null,"Disciplina",null,"512.5"]
[null,null,"Soggetti",null,"Algebras, Linear"]
[{"$nulls":4},"Artificial intelligence - Data processing"]
[{"$nulls":4},"Machine learning"]
[{"$nulls":4},"Mathematical optimization"]
[{"$nulls":4},"Probabilities"]
[{"$nulls":4},"Linear Algebra"]
[{"$nulls":4},"Data Science"]
[{"$nulls":4},"Machine Learning"]
[{"$nulls":4},"Optimization"]
[{"$nulls":4},"Applied Probability"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"Preface -- 1 Vectors -- 2 Inner Product, Orthogonality, Norm -- 3 Matrices -- 4. How Matrices Interact with Inner Products and Norms -- 5 Eigenvalues and Singular Values -- 6 Basics of Optimization -- 7 Introduction to Machine Learning and Data -- 8 Principal Component Analysis -- 9 Graph Theory and Graph-based Learning -- 10 Neural Networks and Deep Learning -- 11 Advanced Optimization -- Bibliography -- Index."]
[null,null,null,"Sommario/riassunto","This text provides a mathematically rigorous introduction to modern methods of machine learning and data analysis at the advanced undergraduate/beginning graduate level. The book is self-contained and requires minimal mathematical prerequisites. There is a strong focus on learning how and why algorithms work, as well as developing facility with their practical applications. Apart from basic calculus, the underlying mathematics — linear algebra, optimization, elementary "]
[{"$nulls":4},"probability, graph theory, and statistics — is developed from scratch in a form best suited to the overall goals. In particular, the wide-ranging linear algebra components are unique in their ordering and choice of topics, emphasizing those parts of the theory and techniques that are used in contemporary machine learning and data analysis. The book will provide a firm foundation to the reader whose goal is to work on applications of machine learning and/or research into the further development of this highly active field of contemporary applied mathematics. To introduce the reader to a broad range of machine learning algorithms and how they are used in real world applications, the programming language Python is employed and offers a platform for many of the computational exercises. Python notebooks complementing various topics in the book are available on a companion GitHub site specified in the Preface, and can be easily accessed by scanning the QR codes or clicking on the links provided within the text. Exercises appear at the end of each section, including basic ones designed to test comprehension and computational skills, while others range over proofs not supplied in the text, practical computations, additional theoretical results, and further developments in the subject. The Students’ Solutions Manual may be accessed from GitHub. Instructors may apply for access to the Instructors’ Solutions Manual from the link supplied on the text’s Springer website. The book can be used in a junior or senior level course for students majoring in mathematics with a focus on applications as well as students from other disciplines who desire to learn the tools of modern applied linear algebra and optimization. It may also be used as an introduction to fundamental techniques in data science and machine learning for advanced undergraduate and graduate students or researchers from other areas, including statistics, computer science, engineering, biology, economics and finance, and so on."]