Radar signal deinterleaving process is a method of classifying intensive pulse streams. The performance of signal classifiers requires to be improved when being confronted with the large amount of data and mode-switch emitters. Recurrent neural network is appropriate as a classifier for pulse streams. However it is weak of long-term dependencies. The forget gate which is a custom function in JANET overcomes the problem. In this paper, JANET is introduced as a classifier for mining the long-term temporal patterns, and the result proves the breathtaking performance of the proposed method.
JIANG Zaiyang
,
SUN Siyue
,
LI Huawang
,
LIANG Guang
. A method for deinterleaving based on JANET[J]. Journal of University of Chinese Academy of Sciences, 2021
, 38(6)
: 825
-831
.
DOI: 10.7523/j.issn.2095-6134.2021.06.013
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