Neural computing architectures : the design of brain-like machines

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Tác giả: Igor Aleksander

Ngôn ngữ: eng

ISBN-10: 0262011107

ISBN-13: 978-0262255592

Ký hiệu phân loại: 006.3 Artificial intelligence

Thông tin xuất bản: Cambridge, Massachusetts : MIT Press, 1989.

Mô tả vật lý: 1 PDF (401 pages) : , illustrations.

Bộ sưu tập: Tài liệu truy cập mở

ID: 313268

 McClelland and Rumelhart's Parallel Distributed Processing was the first book to present a definitive account of the newly revived connectionist/neural net paradigm for artificial intelligence and cognitive science. While Neural Computing Architectures addresses the same issues, there is little overlap in the research it reports. These 18 contributions provide a timely and informative overview and synopsis of both pioneering and recent European connectionist research. Several chapters focus on cognitive modeling
  however, most of the work covered revolves around abstract neural network theory or engineering applications, bringing important complementary perspectives to currently published work in PDP.In four parts, chapters take up neural computing from the classical perspective, including both foundational and current work
  the mathematical perspective (of logic, automata theory, and probability theory), presenting less well-known work in which the neuron is modeled as a logic truth function that can be implemented in a direct way as a silicon read only memory. They present new material both in the form of analytical tools and models and as suggestions for implementation in optical form, and summarize the PDP perspective in a single extended chapter covering PDP theory, application, and speculation in US research. Each part is introduced by the editor.
Includes bibliographical references (p. 381-393).
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