Buscar
Mostrando publicaciones 1-6 de 6
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 ...
Extreme learning machines to combat phase noise in RoF-OFDM schemes
(2019)
Radio-over-fiber (RoF) orthogonal frequency division multiplexing (OFDM) systems have been revealed as the solution to support secure, cost-effective, and high-capacity wireless access for the future telecommunication ...
Parallel training of a set of online sequential extreme learning machines
(2022)
Size databases have constantly increased from advances in technology and the Internet, so processing this vast amount of information has been a great challenge. The neural network Extreme Learning Machine (ELM) have been ...
A new fast training algorithm for autoencoder neural networks based on extreme learning machine
(2022)
Autoencoders are neural networks that are characterized by having the same inputs and outputs. This kind of Neural Networks aim to estimate a nonlinear transformation whose parameters allow to represent the input patterns ...
Fingerprint classification with the extreme learning machine algorithm for multilayer perceptron
(2022)
Fingerprint classification comes to be a relevant guarantee for efficient as well as accurate fingerprint identification, in particular in the case of dealing with one-to-many fingerprint identification. Nevertheless, owing ...
Fast tuning of extreme learning machine neural networks based with simple optimization algorithms
(2022)
Extreme Learning Machine (ELM) is a neural network training paradigm that is characterized by simplicity, speed and high level of accuracy. The tuning of the network parameters is normally carried out with non-linear ...