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Received:January 09, 2018 Revised:January 31, 2018
Received:January 09, 2018 Revised:January 31, 2018
中文摘要: 深度学习是机器学习的一个分支，开创了神经网络发展的新纪元.自编码算法作为深度学习结构的重要组成部分，在无监督学习及非线性特征提取过程中起到了至关重要的作用.首先介绍自编码算法的基本概念及原理，然后介绍基于自编码算法的改进算法，最后列举了自编码算法在若干领域应用的知名案例和发展趋势.
Abstract:Deep learning is a branch of machine learning, creating a new era in the development of neural networks. As an important part of deep learning structure, self-coding algorithm plays a crucial role in unsupervised learning and nonlinear feature extraction. Firstly, the basic concepts and principles of self-encoding algorithm are introduced. Then, the improved algorithm based on self-encoding algorithm is presented. Finally, the well-known cases and development trends of self-encoding algorithm applied in several fields are elaborated.
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基金项目:2017年黑龙江省教育科研专项（2017-0001）
引用文本：
崔广新,李殿奎.基于自编码算法的深度学习综述.计算机系统应用,2018,27(9):47-51
CUI Guang-Xin,LI Dian-Kui.Overview on Deep Learning Based on Automatic Encoder Algorithms.COMPUTER SYSTEMS APPLICATIONS,2018,27(9):47-51
崔广新,李殿奎.基于自编码算法的深度学习综述.计算机系统应用,2018,27(9):47-51
CUI Guang-Xin,LI Dian-Kui.Overview on Deep Learning Based on Automatic Encoder Algorithms.COMPUTER SYSTEMS APPLICATIONS,2018,27(9):47-51
