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Turing's Connectionism : an Investigation of Neural Network Architectures

Autor: Christof Teuscher
Editorial: London : Springer London, 2002.
Serie: Discrete mathematics and theoretical computer science.
Edición/Formato:   Libro-e : Documento : Inglés (eng)Ver todas las ediciones y todos los formatos
Resumen:
Turing's connectionism provides a detailed and in-depth analysis of Turing's almost forgotten ideas on connectionist machines. In a little known paper entitled "Intelligent Machinery", Turing already investigated connectionist models as early as 1948. Unfortunately, his work was dismissed by his employer as a "schoolboy essay" and went unpublished until 1968, 14 years after his death. In this book, Christof Teuscher  Leer más
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Detalles

Género/Forma: Electronic books
Formato físico adicional: Print version:
Tipo de material: Documento, Recurso en Internet
Tipo de documento Recurso internet, Archivo de computadora
Todos autores / colaboradores: Christof Teuscher
ISBN: 9781447101611 1447101618
Número OCLC: 853258570
Nota del idioma: English.
Descripción: 1 online resource (xxiv, 200 pages).
Contenido: Introduction --
Intelligent Machinery --
Synthesis of logical functions and digital systems with Turing networks --
Organizing unorganized machines --
Network Properties and characteristics --
Epilogue.
Título de la serie: Discrete mathematics and theoretical computer science.
Responsabilidad: by Christof Teuscher.

Resumen:

Turing's connectionism provides a detailed and in-depth analysis of Turing's almost forgotten ideas on connectionist machines. In a little known paper entitled "Intelligent Machinery", Turing already investigated connectionist models as early as 1948. Unfortunately, his work was dismissed by his employer as a "schoolboy essay" and went unpublished until 1968, 14 years after his death. In this book, Christof Teuscher analyzes all aspects of Turing's "unorganized machines". Turing himself also proposed a sort of genetic algorithm to train the networks. This idea has been resumed by the author and genetic algorithms are used to build and train Turing's unorganized machines. Teuscher's work starts from Turing's initial ideas, but importantly goes beyond them. Many new kinds of machines and new aspects are considered, e.g., hardware implementation, analysis of the complex dynamics of the networks, hypercomputation, and learning algorithms.

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