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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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