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Nikolaev et al., 2003 - Google Patents

Learning polynomial feedforward neural networks by genetic programming and backpropagation

Nikolaev et al., 2003

Document ID
696440720123966710
Author
Nikolaev N
Iba H
Publication year
Publication venue
IEEE transactions on Neural Networks

External Links

Snippet

This paper presents an approach to learning polynomial feedforward neural networks (PFNNs). The approach suggests, first, finding the polynomial network structure by means of a population-based search technique relying on the genetic programming paradigm, and …
Continue reading at ieeexplore.ieee.org (other versions)

Classifications

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    • G06N3/06Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons
    • G06N3/063Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons using electronic means
    • G06N3/0635Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons using electronic means using analogue means
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
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    • G06N3/082Learning methods modifying the architecture, e.g. adding or deleting nodes or connections, pruning
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    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
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