A New UWB Target Detection and Identification Method Based on Extreme Learning Machine

Author:

Shen Hao,Jiang Ting

Publisher

Springer International Publishing

Reference9 articles.

1. Yanfei S (2009) Combined neural network and PCA for complicate d damage detection of bridge. Nat Comput 2:524–528

2. Young Hoon Choi, Yoon Hyun Kim (2012) “Novel transmission algorithm of UWB signals for WBAN applications”, Consumer Electronics, p 374–375

3. Junqin He, Ting Jiang, Zhihao Xing (2012) A method of target detection and identification based on RPROP and UWB channel characteristic parameters. 2012 I.E. Globecom Workshop: Radar and Sonar Networks—RSN. 12, p 1460–1463

4. Huang G-B, Zhu Q-Y, Siew C-K (2004) Extreme learning machine: a new learning scheme of feedforward neural networks. In 2004 international joint conference on neural networks (IJCNN’2004), Budapest, Hungary, 25–29 Jul 2004

5. Huang G-B, Chen L, Siew C-K (2006) Universal approximation using incremental constructive feedforward networks with random hidden nodes. IEEE Trans Neural Netw 17(4):879–892

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1. Application of optical fiber sensing technology in bridge detection;Highlights in Science, Engineering and Technology;2022-09-30

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