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Mostrando publicaciones 1-7 de 7
Neuroevolution-based adaptive antenna array beamforming scheme to improve the V2V communication performance at intersections
(2021)
The opportunistic exchange of information between vehicles can significantly contribute to reducing the occurrence of accidents and mitigating their damages. However, in urban environments, especially at intersection ...
Multilayer extreme learning machine as equalizer in OFDM-based radio-over-fiber systems
(2021)
Mobile/wireless networks aim to support diverse services with numerous and sophisticated requirements, such as energy efficiency, spectral efficiency, negligible latency, robustness against time and frequency selective ...
Semi-supervised extreme learning machine channel estimator and equalizer for vehicle to vehicle communications
(2021)
Wireless vehicular communications are a promising technology. Most applications related to vehicular communications aim to improve road safety and have special requirements concerning latency and reliability. The traditional ...
Extreme learning machine-based receiver for multi-user massive MIMO systems
(2021)
An extreme learning machine (ELM)-based receiver for multi-user massive MIMO systems is introduced. The proposed ELM combining method, defined in the complex plane, is designed to directly perform MIMO combining processing ...
A multi-channel speech enhancement method based on subband affine projection algorithm in combination with proposed circular nested microphone array
(2021)
In this paper, a novel multi-channel speech enhancement system is introduced based on a proposed circular nested microphone array (C-NMA) in combination with subband affine projection algorithm (SB-APA). The multi-channel ...
Analysis of spectrum detection and decision using machine learning algorithms in cognitive mobile radio networks
(2021)
In this work, the performance of four Machine Learning Algorithms (MLAs) applied to Cognitive Mobile Radio Networks (CMRNs) are analyzed. These algorithms are Coalition Game Theory (CGT), Naive Bayesian Classifier (NBC), ...
Training strategies to minimize interchannel interference effects using supervised learning in gridless Nyquist-WDM systems
(2021)
The dynamism envisioned in future high-capacity gridless optical networks requires facing several challenges in distortion mitigation, such as the mitigation of interchannel interference (ICI) effects in any optical channel ...