%0 Journal Article %1 journals/ejasp/YanJHSL23 %A Yan, Kang %A Jin, Weidong %A Huang, Yingkun %A Song, Pucha %A Li, Zhenhua %D 2023 %J EURASIP J. Adv. Signal Process. %K dblp %N 1 %P 94 %T Deep adaptive temporal network (DAT-Net): an effective deep learning model for parameter estimation of radar multipath interference signals. %U http://dblp.uni-trier.de/db/journals/ejasp/ejasp2023.html#YanJHSL23 %V 2023

@article{journals/ejasp/YanJHSL23, added-at = {2023-10-14T00:00:00.000+0200}, author = {Yan, Kang and Jin, Weidong and Huang, Yingkun and Song, Pucha and Li, Zhenhua}, biburl = {https://www.bibsonomy.org/bibtex/2d9b606a467babfcb8cc6326360ec8de5/dblp}, ee = {https://doi.org/10.1186/s13634-023-01053-8}, interhash = {c49fc9cce70d26785e11900af5a399f3}, intrahash = {d9b606a467babfcb8cc6326360ec8de5}, journal = {EURASIP J. Adv. Signal Process.}, keywords = {dblp}, month = {December}, number = 1, pages = 94, timestamp = {2024-04-09T06:58:11.000+0200}, title = {Deep adaptive temporal network (DAT-Net): an effective deep learning model for parameter estimation of radar multipath interference signals.}, url = {http://dblp.uni-trier.de/db/journals/ejasp/ejasp2023.html#YanJHSL23}, volume = 2023, year = 2023 }