| Feynman And Computation Revised Edition Contributor(s): Hey, Anthony (Author) |
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ISBN: 081334039X ISBN-13: 9780813340395 Publisher: CRC Press OUR PRICE: $92.14 Product Type: Paperback Published: June 2002 Annotation: A tribute to Feynman and a new exploration of the limits of computers by some of today's most influential scientists The contributors include Charles Bennett on Quantum Information Theory, Geoffrey Fox on Internetics, Norman Margolus on Crystalline Computation, and Tommaso Toffoli on the Fungibility of Computation. Both a tribute to Feynman and a new exploration of the limits of computers by some of today's most influential scientists, Feynman and Computation continues the pioneering work started by Feynman and published by him in his own Lectures on Computation. This new computation volume consists of both original chapters and reprints of classic papers by leaders in the field. Feynman and Computation will generate great interest from the scientific community and provide essential background for further work in this field. |
| Additional Information |
| BISAC Categories: - Science | Physics - General |
| Dewey: 004 |
| LCCN: 2007310126 |
| Series: Frontiers in Physics |
| Physical Information: 1.11" H x 6.2" W x 9.02" (1.54 lbs) 464 pages |
| Descriptions, Reviews, Etc. |
| Publisher Description: Computational properties of use to biological organisms or to the construction of computers can emerge as collective properties of systems having a large number of simple equivalent components (or neurons). The physical meaning of content-addressable memory is described by an appropriate phase space flow of the state of a system. A model of such a system is given, based on aspects of neurobiology but readily adapted to integrated circuits. The collective properties of this model produce a content-addressable memory which correctly yields an entire memory from any subpart of sufficient size. The algorithm for the time evolution of the state of the system is based on asynchronous parallel processing. Additional emergent collective properties include some capacity for generalization, familiarity recognition, categorization, error correction, and time sequence retention. The collective properties are only weakly sensitive to details of the modeling or the failure of individual devices. |