Title
Neural Network Processing For Adaptive Array Antennas
Abstract
Currently, several algorithms can be used to perform the direction finding or angle of arrival of signals from mobile users. One drawback of these algorithms is the difficulty of their implementation in real-time because of their intensive computational complexity. Neural networks, on the other hand, due to their high-speed computational capability, can yield results in real-time. Moreover, conventional beamformers require highly calibrated antennas with identical element properties. Performance degradation often occurs due to the fact that these algorithms poorly adapt to element failure or other sources of errors. Neural network-based array antennas do not suffer from this shortcoming.
Publication Date
1-1-1999
Publication Title
IEEE Antennas and Propagation Society International Symposium: Wireless Technologies and Information Networks, APS 1999 - Held in conjunction with USNC/URSI National Radio Science Meeting
Volume
4
Number of Pages
2584-2587
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1109/APS.1999.789337
Copyright Status
Unknown
Socpus ID
84951975289 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/84951975289
STARS Citation
Christodoulou, C. G.; El Zooghby, A. H.; and Georgiopoulos, M., "Neural Network Processing For Adaptive Array Antennas" (1999). Scopus Export 1990s. 3795.
https://stars.library.ucf.edu/scopus1990/3795