Learning by neural networks
Keywords
neural network
parallel distributed processing
linear separability
perceptron
pattern discrimination
pattern classification
back propagation error learning
hidden unit
generalized delta rule
pattern recognition
competitive learning
Hopfield network
optimization problem
traveling salesperson problem
Boltzmann machine
annealing
n-queen problem
relaxation method
Markovian random field
image restoration
parallel computation
massively parallel computation
In this chapter, we describe algorithms for learning using neural networks. A neural network is a kind of computation system in which a state of the system is represented as a numerical distribution pattern with many processing units and connections among ...
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