Optimal Hardware Implementation of a Feedforward Neural Network Topology using a Genetic Algorithm for Prunning

The genetic algorithms are an important part of modern global searching methods class with specific applications in the complex optimization problems. This paper proposes an interesting approach of feedforward neural network topology optimization based on a new fitness function definition. The exper...

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Main Authors: Vizitiu, C.I., Radu, A., Oroian, T., Molder, C.
Format: Conference Proceeding
Language:English
Subjects:
Biological cells
Convergence
Encoding
Feedforward neural networks
Genetic algorithms
Network topology
Neural network hardware
Neural networks
Neurons
Optimization methods
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creator Vizitiu, C.I.
Radu, A.
Oroian, T.
Molder, C.
description The genetic algorithms are an important part of modern global searching methods class with specific applications in the complex optimization problems. This paper proposes an interesting approach of feedforward neural network topology optimization based on a new fitness function definition. The experimental results getting in this case are compared with ones from a classic pruning method, and for their validation a proper hardware implementation of the used networks is indicated.
doi_str_mv 10.1109/SMICND.2007.4519759
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subjects Biological cells
Convergence
Encoding
Feedforward neural networks
Genetic algorithms
Network topology
Neural network hardware
Neural networks
Neurons
Optimization methods
title Optimal Hardware Implementation of a Feedforward Neural Network Topology using a Genetic Algorithm for Prunning
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