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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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Збережено в:
Автори: Guangxing Tai, Yanhua Wang, Yang Li, Wei Hong
Формат: Artigo
Мова:Inglês
Опубліковано: Wiley 2019-09-01
Серія:The Journal of Engineering
Предмети:
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
Онлайн доступ:https://digital-library.theiet.org/content/journals/10.1049/joe.2019.0741
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