Development and application of a deep learning–based sparse autoencoder framework for structural damage identification

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Development and application of a deep learning–based sparse autoencoder framework for structural damage identification

© The Author(s) 2018. This article proposes a deep sparse autoencoder framework for structural damage identification. This framework can be employed to obtain the optimal solutions for some pattern recognition problems with highly nonlinear nature, such as learning a mapping between the vibration ch...

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Bibliographic Details
Main Authors:	Pathirage, C., Li, Jun, Li, L., Hao, Hong, Liu, Wan-Quan, Wang, R.
Format:	Journal Article
Published:	Sage Publications 2019
Online Access:	http://hdl.handle.net/20.500.11937/74812

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