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Five-fold cross-validation results of mulit-scale CNN algorithm at different SNRs.

Five-fold cross-validation results of mulit-scale CNN algorithm at different SNRs.

<p>Five-fold cross-validation results of mulit-scale CNN algorithm at different SNRs.</p>

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Bibliographic Details
Main Author: Jiuxiao Cao (21594403) (author)
Other Authors: Rui Zhu (305217) (author), Zhen Wang (72451) (author), Jun Wang (5906) (author), Guohao Shi (21594406) (author), Peng Chu (5565407) (author)
Published: 2025
Subjects:
Space Science
Biological Sciences not elsewhere classified
spatial feature diversity
sequential learning capacity
remote communications due
hybrid architecture enhances
evaluated using five
ensure statistical reliability
different receptive fields
dataset includes 45
common shortwave protocols
captures temporal dependencies
3gale &# 8212
000 labeled samples
subcarrier modulations based
scale convolutional gru
robust signal classification
subcarrier classification
low signal
world sources
vital role
time deployment
study proposes
standard gpu
selective fading
scalable solution
results show
results confirm
range capabilities
protocol identification
noise ratios
multipath propagation
inference time
gru provides
fold cross
disaster relief
dimensional representations
bidirectional gru
based real
8 db
10 db
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