Abstract:

Artificial neural networks are increasingly closely related to other subject areas. People solve problems in various fields by exploring and improving the layer structure of artificial neural networks. Based on the analysis of artificial neural networks related literature, this paper summarizes the history of artificial neural network growth and presents relevant principles of artificial neural networks based on the development of neural networks, including multilayer perceptron, back-propagation algorithm, convolutional neural network and recurrent neural network, explains the classic convolutional neural network model in the development of the convolutional neural network and the widely used variant network structure in the recurrent neural network, reviews the application of each artificial neural network algorithm in related fields, summarizes the possible direction of development of the artificial neural network.

Key words: artificial neural network, multilayer perceptron, recurrent neural network

摘要：

人工神经网络与其他学科领域联系日益紧密，人们通过对人工神经网络层结构的探索和改进来解决各个领域的问题。根据人工神经网络相关文献进行分析，综述了人工神经网络算法以及网络模型结构的发展史，根据神经网络的发展介绍了人工神经网络相关概念，其中主要涉及到多层感知器、反向传播神经网络、卷积神经网络以及递归神经网络，描述了卷积神经网络发展当中出现的部分卷积神经网络模型和递归神经网络中常用的相关网络结构，分别综述了各个人工神经网络算法在相关领域的应用情况，总结了人工神经网络的未来发展方向。

关键词: 人工神经网络, 多层感知器, 递归神经网络