Open Access
Issue |
JNWPU
Volume 41, Number 6, Decembre 2023
|
|
---|---|---|
Page(s) | 1134 - 1145 | |
DOI | https://doi.org/10.1051/jnwpu/20234161134 | |
Published online | 26 February 2024 |
- PING Fulong. Joint DOA and polarization estimation algorithm researching for polarization sensetive conformal array antenna[D]. Chengdu: University of Electronic Science and Technology of China, 2016 (in Chinese) [Google Scholar]
- JIANG Yadong. DOA estimation of coherent source and array calibration for airborne[D]. Chengdu: University of Electronic Science and Technology of China, 2021 (in Chinese) [Google Scholar]
- WU Di. Research on array errors calibration and direction of arrival estimation[D]. Harbin: Harbin Engineering University, 2015 (in Chinese) [Google Scholar]
- LIU Shiyan, ZHANG Zhi, GUO Yu. 2-D DOA estimation with imperfect L-shaped array using active calibration[J]. IEEE Communications Letters, 2021, 25(4): 1178–1182 [Article] [CrossRef] [Google Scholar]
- ZHANG Ke, CHENG Juming, FU Jin. Fast active error calibration algorithm for array chanel uncertainty[J]. Journal of Electronics & Information Technology, 2015, 37(9): 2110–2116 (in Chinese) [Google Scholar]
- NG B P, LIE J P, ER M H, et al. A practical simple geometry and gain/phase calibration technique for antenna array processing[J]. IEEE Trans on Antennas and Propagation, 2009, 57(7): 1963–1972. [Article] [NASA ADS] [CrossRef] [Google Scholar]
- JIANG Zuqing, YANG Bin. Novel multiplicative array errors active calibration algorithm in presence of multipath[J]. Journal of Information Engineering University, 2022, 23(2): 129–134 (in Chinese) [Google Scholar]
- ZHAO Zheng, TIAN Weiming, DENG Yunkai, et al. Calibration method of array errors for wideband MIMO imaging radar based on multiple prominent targets[J]. Remote Sensin, 2021, 13(15): 2997. [Article] [NASA ADS] [CrossRef] [Google Scholar]
- LIN Xiao. Research on self-correction technology for gain-phase error in polarization-sensitive array[J]. Harbin: Harbin Institute of Technology, 2020 (in Chinese) [Google Scholar]
- LIU H, ZHAO L, LI Y, et al. A sparse-based approach for DOA estimation and array calibration in uniform linear array[J]. IEEE Sensors Journal, 2016, 16(15): 1–5. [Article] [Google Scholar]
- TUNCER E, FRIEDLANDER B. Classical and modern direction-of-arrival estimation[J]. Applied Acoustics, 2009, 71(5): 493 [Google Scholar]
- RUMELHART D E, HINTON G E, WILLIAMS R J. Learning representations by back-propagating errors[J]. Nature, 1986, 323(6088): 533–536 [CrossRef] [Google Scholar]
- NG A. Sparse autoencoder[J]. CS294A Lecture Notes, 2011, 72(1): 1–19 [Google Scholar]
- VINCENT P, LAROCHELLE H, LAJOIE I, et al. Stacked denoising autoencoders: learning useful representations in a deep network with a local denoising criterion[J]. Journal of Machine Learning Research, 2010, 11(12): 3371–3408 [Google Scholar]
- RIFAI S, VINCENT P, MULLER X, et al. Contractive auto-encoders: explicit invariance during feature extraction[C]//Proceedings of the 28th International Conference on Machine Learning, 2011: 833–840 [Google Scholar]
- KINGMA D P, WELLING M. Auto-encoding variational Bayes[J/OL](2022-12-10)[2023-01-01]. [Article] [Google Scholar]
- MIAN P, JIE J, ZHU L, et al. Radar HRRP recognition based on discriminant deep autoencoders with small training data size[J]. Electronics Letters, 2016, 52(20): 1725–1727. [Article] [CrossRef] [Google Scholar]
- WANG Chen, ZHANG Diming, HAN Bin. An industrial intrusion detection algorithm based on variational autoencoder and three-way decisions[J]. NETwork and Information Security, 2022, 41(6): 10–17 (in Chinese) [Google Scholar]
- ZHANG Y Y, GAO L, LI X Y, et al. A novel data-driven fault diagnosis method based on deep learning[C]//International Conference on Data Mining and Big Data, 2017: 442–452 [Google Scholar]
- WANG Yongliang, CHEN Hui, PENG Yingning, et al. Spatial spectrum estimation theory and algorithms[M]. Beijing: Tsinghua University Press, 2004: 19–20 (in Chinese) [Google Scholar]
- CUI Wei. Research on error correction of array antenna based on improved particle swarm algorithm[D]. Zhengjiang: Jiangsu University of Science and Technology, 2020 (in Chinese) [Google Scholar]
- GLOROT X, BORDES A, BENGIO Y. Deep spare rectifier neural networks[C]//Proceedings of the 14th International Conference on Artificial Intelligence and Statistics, 2011: 315–323 [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.