Radar HRRP target recognition based on stacked denosing sparse autoencoder

An end-to-end radar high-resolution range profile recognition method is proposed based on stacked denosing sparse autoencoder which stacks several denosing sparse autoencoders and uses softmax as the classifier. The training process consists of two steps. The first is layer-by-layer pre-training and...

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Detalhes bibliográficos

Principais autores:	Guangxing Tai, Yanhua Wang, Yang Li, Wei Hong
Formato:	Artigo
Idioma:	Inglês
Publicado em:	Wiley 2019-09-01
coleção:	The Journal of Engineering
Assuntos:	learning (artificial intelligence) feature extraction radar target recognition neural nets signal denoising stacked denosing sparse autoencoder end-to-end radar high-resolution range profile recognition method sparse autoencoders layer-by-layer pre-training pre-training results two-step training process radar hrrp target recognition
Acesso em linha:	https://digital-library.theiet.org/content/journals/10.1049/joe.2019.0741
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