量子启发二进制神经网络算法

O. Patel, Aruna Tiwari
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引用次数: 12

摘要

本文提出了一种新的基于量子的二元神经网络学习算法。形成三层网络结构。该方法利用量子概念更新和确定神经元权值,适用于两类问题。利用量子概念形成优化的网络结构。在神经元数量和分类精度方面也得到了提高。并与基于量子的人工神经网络优化算法(QANN)进行了比较。结果表明,该方法在隐层神经元数、迭代次数、训练精度和泛化精度等方面均有提高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Quantum Inspired Binary Neural Network Algorithm
In this paper a novel quantum based binary neural network learning algorithm is proposed. It forms three layer network structure. The proposed method make use of quantum concept for updating and finalizing weights of the neurons and it works for two class problem. The use of quantum concept form an optimized network structure. Also performance in terms of number of neurons and classification accuracy is improved. Same is compared with a quantum-based algorithm for optimizing artificial neural networks algorithm (QANN). It is found that there is improvement in the form of number of neurons at hidden layer, number of iterations, training accuracy and generalization accuracy.
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