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The Research of Alphabet Identification Based on Genetic BP Neural Network

机译:基于遗传BP神经网络的字母识别研究

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The Back Propagation (BP) neural network genetic algorithm was used to identify alphabet, and the new algorithm combine the advantages of both genetic algorithm and the BP neural network. Genetic learning algorithm was used for the global optimization and BP training algorithm to accurately optimize the neural network weights and training the neural network to learn letter recognition algorithm. Add-noise alphabet of MATLAB simulation results show that the new network error recognition rate reduced by 10% compared to BP neural network and the recognition speed is also faster than the traditional BP neural network with accuracy and fast convergence.
机译:BP(BP)神经网络遗传算法被用来识别字母,新算法结合了遗传算法和BP神经网络的优点。遗传学习算法被用于全局优化和BP训练算法,以准确地优化神经网络权重并训练神经网络学习字母识别算法。 MATLAB仿真结果的加噪字母表表明,与BP神经网络相比,新的网络错误识别率降低了10%,并且识别速度也比传统的BP神经网络更快,并且准确性高且收敛速度快。

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