This study presents a transfer function (TF) approach based on the continuous wavelet transform (CWT) using the vibration measurements for feature extraction.
From five-component magnetotelluric data recorded at onshore and offshore locations furing the EMSLAB experiment, we derive transfer functions using various techniques.
We present an innovative transfer learning method for classifying risky events with scarce state of polarization (SOP) data, utilizing a deep convolutional neural network pre-trained on unrelated i
Machine learning (ML) applications for wireless communication has gained momentum on the standardization discussions for 5G advanced and beyond.
The ability to predict the quality of a wireless channel is fundamental to enable anticipatory networking tasks.
Long term accurate and efficient resource utilization predictions are of vital importance for the future generation of mobile wireless networks.
Fifth generation wireless networks (5G) will face key challenges caused by diverse patterns of traffic demands and massive deployment of heterogeneous access points.
Network slicing technology in next-generation RAN dedicates to supporting variant requirements of the network services.
We present characterization results of a pair 10-mode spatial multiplexers based on multi-plane light conversion by employing a swept-wavelength interferometer.
A major obstacle in the performance analysis of product-form cellular systems is the evaluation of the normalizing factor, or partition function.
