Results 111 to 120 of about 1,760 (173)

Hybrid robust beamforming for enhanced multiple moving object detection with phased array scanning radar. [PDF]

Sci Rep
Islam SS, Hossain MS, Islam S, Hasan R.
europepmc   +1 more source

Echo- and Image-Domain Fusion for Micro-Leak Detection and Localization in Subsea Gas Pipelines. [PDF]

Sensors (Basel)
Liu H, Li J, Jiang X, Luo Y.
europepmc   +1 more source

Distributed Antenna Array and RIS-Assisted Planning Framework for Intelligent Coverage Optimization in B5G/6G Cell-Free Massive MIMO. [PDF]

Sensors (Basel)
Farre V, Vega-Sánchez J, Cama-Pinto A, Pacheco VG, Orozco Garzón N, Flores-Moyano R.   +5 more
europepmc   +1 more source

AI-driven dynamic resource allocation for ISAC systems in 6G networks: intelligent beamforming, interference management, and power allocation. [PDF]

Sci Rep
Aman M, Rehman GU, Zubair M, Alfakeeh A, Aboulola OI, Daud A.   +5 more
europepmc   +1 more source

Assessing the benefits of using plane wave compounding when estimating backscatter coefficients with an in situ bead as a calibration target. [PDF]

J Acoust Soc Am
Zhao Y, Kou Z, Liu M, Miller RJ, Czarnota GJ, Oelze ML.   +5 more
europepmc   +1 more source

Leveraging Reconfigurable Massive MIMO Antenna Arrays for Enhanced Wireless Connectivity in Biomedical IoT Applications. [PDF]

Sensors (Basel)
Enahoro S, Ekpo SC, Al-Yasir Y, Uko M.
europepmc   +1 more source

Massive MIMO joint beamforming and power allocation via LMS with narwhal lemming optimization and fractional ResNeXt-based control. [PDF]

Sci Rep
Kamal MM, Yinsheng L, Ma T, Samkari HS, Allehyani MF, Sheraz M, Khushik MHAK, Qatawneh M, Chuah TC.   +8 more
europepmc   +1 more source

From EEG Source Localization to Brain Network Analysis: A Computational Neuroscience Perspective. [PDF]

Biology (Basel)
Lee J, Eom TH.
europepmc   +1 more source

BeamCraft: Deep Reinforcement Learning-DrivenMulti-Objective Beamforming for ISAC

Dao DN, Miao Y.
europepmc   +1 more source

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Robust Adaptive Beamforming

IEEE Transactions on Acoustics, Speech, and Signal Processing, 1987
Adaptive beamforming algorithms can be extremely sensitive to slight errors in array characteristics. Errors which are uncorrelated from sensor to sensor pass through the beamformer like uncorrelated or spatially white noise. Hence, gain against white noise is a measure of robustness.
Henry Cox, Robert M. Zeskind, Mark M. Owen   +2 more
exaly   +3 more sources