A review of designs and applications of echo state networks
Recurrent Neural Networks (RNNs) have demonstrated their outstanding ability in sequence
tasks and have achieved state-of-the-art in wide range of applications, such as industrial …
tasks and have achieved state-of-the-art in wide range of applications, such as industrial …
Forecasting directional changes in the fx markets
A Bakhach, EPK Tsang… - 2016 IEEE Symposium …, 2016 - ieeexplore.ieee.org
Most of existing studies sample markets' prices as time series when developing models to
predict market's trend. Directional Changes (DC) is an approach to summarize market prices …
predict market's trend. Directional Changes (DC) is an approach to summarize market prices …
Situation awareness and computational intelligence in opportunistic networks to support the data transmission of urban sensing applications
Smart cities can be seen as large-scale Cyber-Physical Systems with sensors monitoring
cyber and physical indicators and with actuators dynamically changing the complex urban …
cyber and physical indicators and with actuators dynamically changing the complex urban …
Using echo state networks to approximate value functions for control
An Echo State Network (ESN) is a type of single-layer recurrent neural network with
randomly-chosen internal weights and a trainable output layer. We prove under mild …
randomly-chosen internal weights and a trainable output layer. We prove under mild …
Channel estimation in wireless OFDM systems using reservoir computing
Reservoir Computing (RC) is a recent neurologically inspired concept for processing time
dependent data that lends itself particularly well to hardware implementation by using the …
dependent data that lends itself particularly well to hardware implementation by using the …
Detection of denial of service attacks using echo state networks
K Bekshentayeva, L Trajković - 2021 IEEE International …, 2021 - ieeexplore.ieee.org
Denial of Service (DoS) and Distributed Denial of Service (DDoS) attacks are major threats
to cybersecurity in communication networks. These cyber attacks are evolving and …
to cybersecurity in communication networks. These cyber attacks are evolving and …
Explorations in echo state networks
A Millea - 2014 - fse.studenttheses.ub.rug.nl
Echo State Networks are powerful recurrent neural networks that can predict time-series
very well. However, they are often unstable, making the process of finding an ESN for a …
very well. However, they are often unstable, making the process of finding an ESN for a …
Forecasting foreign exchange rates using hybrid functional link RBF neural network and Levenberg-Marquardt learning algorithm
This paper proposes a novel nonlinear ensemble forecasting model integrating functional
link (FL) with radial basis function (RBF) neural network in order to improve prediction …
link (FL) with radial basis function (RBF) neural network in order to improve prediction …
[PDF][PDF] Half hourly electricity load prediction using echo state network
S Varshney, T Verma - International Journal of Science and Research, 2014 - Citeseer
Prediction of time series is a task that cannot be efficiently done by using feed forward neural
network. Recurrent neural network are the suitable neural networks for time series prediction …
network. Recurrent neural network are the suitable neural networks for time series prediction …
[PDF][PDF] Echo State Networks for Reinforcement Learning
Abstract An Echo State Network (ESN) is a type of single-layer recurrent neural network with
randomly-chosen internal weights and a trainable output layer. We prove under mild …
randomly-chosen internal weights and a trainable output layer. We prove under mild …