A01=Anthony Hey
Algorithmic Information Content
asynchronous memory retrieval algorithms
Author_Anthony Hey
CA Model
Carver A. Mead
Category=PDX
Category=PH
Category=UY
Cellular Automata
Charles H. Bennett
connection
Connection Machine
content-addressable memory
DIBL
Ed Fredkin
emergent computation
EPR Pair
eq_bestseller
eq_computing
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
eq_science
Feynman Lectures
function
Geoffrey C. Fox
Gerald Jay Sussman
Hilbert Space
John Archibald Wheeler
John J. Hopfield
Landauer's Principle
Landauer’s Principle
machine
Macroscopic Quantum Systems
Marvin Minsky
Maxwell's Demon
Maxwell’s Demon
mechanics
neural network models
Norman Margolus
Parallel Computing
parallel processing systems
parallelism
Paul Benioff
physical entropy theory
Pluto's Orbit
Pluto’s Orbit
potential
quantum
Quantum Algorithms
Quantum Computation
Quantum Error Correction
Quantum Gate
quantum information science
Quantum Logic Operations
Quantum Mechanical System
Quantum Parallelism
Quantum Systems
Quantum Turing Machine
Relative Energy Error
Richard Feynman
Richard J. Hughes
Richard P. Feynman
Rolf Landauer
RSA Problem
systems
Tommaso Toffoli
vector
Vector Potential
W. Daniel Hillis
W. H. Zurek
wave
Product details
- ISBN 9780813340395
- Weight: 453g
- Dimensions: 152 x 229mm
- Publication Date: 27 Jun 2002
- Publisher: Taylor & Francis Inc
- Publication City/Country: US
- Product Form: Paperback
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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.
David Pines is research professor of physics at the University of Illinois at Urbana-Champaign. He has made pioneering contributions to an understanding of many-body problems in condensed matter and nuclear physics, and to theoretical astrophysics. Editor of Perseus' Frontiers in Physics series and former editor of American Physical Society's Reviews of Modern Physics, Dr. Pines is a member of the National Academy of Sciences, the American Philosophical Society, a foreign member of the USSR Academy of Sciences, a fellow of the American Academy of Arts and Sciences, and of the American Association for the Advancement of Science. Dr. Pines has received a number of awards, including the Eugene Feenberg Memorial Medal for Contributions to Many-Body Theory the P.A.M. Dirac Silver Medal for the Advancement of Theoretical Physics and the Friemann Prize in Condensed Matter Physics.
