The convergence of machine learning and communications /

Autor(es):
Samek, Wojciech | Stanczak, Slawomir | Wiegand, Thomas
Editor: Geneva : International Telecommunication Union, 2017Descripción: 10 pTipo de contenido: texto (visual)
Tipo de medio: electrónico
Tipo de soporte: recurso en línea
Tema(s): Tecnologías habilitadoras digitales | Science and TechnologyRecursos en línea: Acceso al documento En: ITU Journal: ICT Discoveries Vol. 2018, no. 1, p. 49-58Resumen: The areas of machine learning and communication technology are converging. Today's communication systems generate a large amount of traffic data, which can help to significantly enhance the design and management of networks and communication components when combined with advanced machine learning methods. Furthermore, recently developed end-to-end training procedures offer new ways to jointly optimize the components of a communication system. Also, in many emerging application fields of communication technology, e.g., smart cities or Internet of things, machine learning methods are of central importance. This paper gives an overview of the use of machine learning in different areas of communications and discusses two exemplar applications in wireless networking. Furthermore, it identifies promising future research topics and discusses their potential impact.
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El Centro de Documentación del Observatorio Nacional de las Telecomunicaciones y de la Sociedad de la Información (CDO) os da la bienvenida al catálogo bibliográfico sobre recursos digitales en las materias de Tecnologías de la Información y telecomunicaciones, Servicios públicos digitales, Administración Electrónica y Economía digital. 

 

 

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The areas of machine learning and communication technology are converging. Today's communication systems generate a large amount of traffic data, which can help to significantly enhance the design and management of networks and communication components when combined with advanced machine learning methods. Furthermore, recently developed end-to-end training procedures offer new ways to jointly optimize the components of a communication system. Also, in many emerging application fields of communication technology, e.g., smart cities or Internet of things, machine learning methods are of central importance. This paper gives an overview of the use of machine learning in different areas of communications and discusses two exemplar applications in wireless networking. Furthermore, it identifies promising future research topics and discusses their potential impact.

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