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Turing's Connectionism : an Investigation of Neural Network Architectures

ผู้แต่ง: Christof Teuscher
สำนักพิมพ์: London : Springer London, 2002.
ชุด: Discrete mathematics and theoretical computer science.
ครั้งที่พิมพ์/รูปแบบ:   หนังสืออีเล็กทรอนิกส์ : เอกสาร : ภาษาอังกฤษดูครั้งที่พิมพ์และรูปแบบ
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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 Unfortunately, his work was dismissed by his employer as a "schoolboy essay" and went unpublished until 1968, 14 years after his death.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  อ่านมากขึ้น…
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รูปแบบทางกายภาพเพิ่มเติม Print version:
ขนิดวัสดุ: เอกสาร, ทรัพยากรอินแทอร์เน็ต
ประเภทเอกสาร แหล่งข้อมูลอินเทอร์เน็ต, ไฟล์คอมพิวเตอร์
ผู้แต่งทั้งหมด : ผู้แต่งร่วม Christof Teuscher
ISBN: 9781447101611 1447101618
OCLC Number: 853258570
หมายเหตุถาษา: English.
คำอธิบาย: 1 online resource (xxiv, 200 pages).
สารบัญ: Introduction --
Intelligent Machinery --
Synthesis of logical functions and digital systems with Turing networks --
Organizing unorganized machines --
Network Properties and characteristics --
Epilogue.
ชื่อชุด: Discrete mathematics and theoretical computer science.
ความรับผิดชอบ: by Christof Teuscher.

บทคัดย่อ:

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 Unfortunately, his work was dismissed by his employer as a "schoolboy essay" and went unpublished until 1968, 14 years after his death.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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