Optimizing Machine Learning Algorithms for Dynamic Direction Finding-Reference-Cited by-同舟云学术

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Optimizing Machine Learning Algorithms for Dynamic Direction Finding

Published:2023-01-10 Issue: Volume: Page:
ISSN:
Container-title:2023 United States National Committee of URSI National Radio Science Meeting (USNC-URSI NRSM)
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Author:

Willis John M.¹,Venkatakrishnan Satheesh B.¹,Volakis John L.¹

Affiliation:

1. Florida International University,Miami,Florida,USA

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10042977/10042984/10043143.pdf?arnumber=10043143

Reference6 articles.

1. Angle-of-Arrival Estimation Using an Adaptive Machine Learning Framework

2. A Compact Machine Learning Architecture for Wideband Amplitude-Only Direction Finding

3. DeepMUSIC: Multiple Signal Classification via Deep Learning

4. Toward Wide-Frequency-Range Direction Finding With Support Vector Regression

5. Coherent SVR Learning for Wideband Direction-of-Arrival Estimation

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Machine Learning Enhancement of a Luneburg Lens Amplitude-Only Direction-Finding Antenna;2023 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting (USNC-URSI);2023-07-23

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