Integer weight training by differential evolution algorithms
نویسنده
چکیده
In this work differential evolution strategies are applied in neural networks with integer weights training. These strategies have been introduced by Storn and Price [Journal of Global Optimization, 11, pp. 341–359, 1997]. Integer weight neural networks are better suited for hardware implementation as compared with their real weight analogous. Our intention is to give a broad picture of the behaviour of this class of evolution algorithms in this difficult task. Simulation results show that this is a promising approach.
منابع مشابه
Evolutionary Algorithms for Integer Weight Neural Network Training
In this work differential evolution strategies are applied in neural networks with integer weights training. These strategies have been introduced by Storn and Price [Journal of Global Optimization, 11, pp. 341–359, 1997]. Integer weight neural networks are better suited for hardware implementation as compared with their real weight analogous. Our intention is to give a broad picture of the beh...
متن کاملNeural Network Training with Constrained Integer Weights
In this contribution we present neural network training algorithms, which are based on the differential evolution (DE) strategies introduced by Storn and Price [Journal of Global Optimization 11, 341-359, 19971. These strategies are applied to train neural networks with small integer weights. Such neural networks are better suited for hardware implementation than the real weight ones. Furthermo...
متن کاملA Differential Evolution and Spatial Distribution based Local Search for Training Fuzzy Wavelet Neural Network
Abstract Many parameter-tuning algorithms have been proposed for training Fuzzy Wavelet Neural Networks (FWNNs). Absence of appropriate structure, convergence to local optima and low speed in learning algorithms are deficiencies of FWNNs in previous studies. In this paper, a Memetic Algorithm (MA) is introduced to train FWNN for addressing aforementioned learning lacks. Differential Evolution...
متن کاملTraining Neural Networks with 3–bit Integer Weights
In this work we present neural network training algorithms, which are based on the differential evolution (DE) strategies introduced by Storn and Price [Journal of Global Optimization. 11:341–359, 1997]. These strategies are applied to train neural networks with 3–bit integer weights. Integer weight neural networks are better suited for hardware implementation than their real weight analogous. ...
متن کاملInteger Weight Higher-Order Neural Network Training Using Distributed Differential Evolution
We study the class of Higher-Order Neural Networks and especially the Pi-Sigma Networks. The performance of Pi-Sigma Networks is evaluated through several well known neural network training benchmarks. In the experiments reported here, Distributed Evolutionary Algorithms for Pi-Sigma networks training are presented. More specifically the distributed version of the Differential Evolution algorit...
متن کامل