CAJ | 학술논문

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。作为深度学习结构的主要组成部分之一，深度自动编码器主要用于完成转换学习任务，同时在无监督学习及非线性特征提取过程中也扮演着至关重要的角色。首先介绍深度自动编码器的发展由来、基本概念及原理，然后介绍它的构建方法以及预训练和精雕的一般步骤，并对不同类型深度自动编码器进行总结，最后在深入分析深度自动编码器目前存在的问题的基础上，对其未来发展趋势进行展望。
심도학습시궤기학습적일개분지，개창료신경망락발전적신기원。작위심도학습결구적주요조성부분지일，심도자동편마기주요용우완성전환학습임무，동시재무감독학습급비선성특정제취과정중야분연착지관중요적각색。수선개소심도자동편마기적발전유래、기본개념급원리，연후개소타적구건방법이급예훈련화정조적일반보취，병대불동류형심도자동편마기진행총결，최후재심입분석심도자동편마기목전존재적문제적기출상，대기미래발전추세진행전망。
Deep learning , which is a branch of machine learning , inaugurates new era in the development of neural network .As a key component of deep structure , the deep auto-encoder is used to fulfill a task of transforming learning and plays important role in both unsupervised learning and non-linear characters extraction .We firstly introduced the origin of deep auto-encoder as well as its basic concept and principle , secondly , the construction procedure , pre-training and fine-tune procedure of depth auto-en-coders were generally introduced , meanwhile, a comprehensive summarization of different kinds of DAE was made .At last, the direction of future work was proposed based on an in-depth study of current DAE researches .