Parallel Models of Associative Memory
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Associative Memory
Associative Net
Associative Recall
Average Firing Rate
Average Membrane Potential
Category=JMR
cell
COLOR COLOR COLOR
connectionist learning
CONNECTIONIST Model
Direction Primitives
DISTRIBUTED MEMORY SYSTEMS
eq_bestseller
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eq_isMigrated=2
eq_nobargain
eq_non-fiction
eq_society-politics
field
Hidden Units
High Dimensional Environment
High Order Statistics
inductive generalization
Inductive Net
JOHN FATHER
Memory Search
National Academy
net
networks
neural
neural computation
Pairwise Covariances
parallel neural processing mechanisms
Past Tenses
pyramidal
Reaction Time
Reaction Time Distributions
recall
receptive
Receptive Fields
Retrieve Inform Ation
self-organizing systems
Semantic Net
semantic networks
Sim Ilarities
state
vectors
visual memory modeling
Von Neumann Machine
Product details
- ISBN 9780805802702
- Weight: 680g
- Dimensions: 152 x 229mm
- Publication Date: 01 Jan 1989
- Publisher: Taylor & Francis Inc
- Publication City/Country: US
- Product Form: Paperback
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This update of the 1981 classic on neural networks includes new commentaries by the authors that show how the original ideas are related to subsequent developments. As researchers continue to uncover ways of applying the complex information processing abilities of neural networks, they give these models an exciting future which may well involve revolutionary developments in understanding the brain and the mind -- developments that may allow researchers to build adaptive intelligent machines. The original chapters show where the ideas came from and the new commentaries show where they are going.
Geoffrey E. Hinton, James A. Anderson
