Constructing non-invasive Brain-Computer Interfaces (BCI) that are practical for use in assistive technology has proven to be a challenging problem. We assert that classification algorithms that are capable of capturing sophisticated spatiotemporal patterns in Electroencephalography (EEG) signals are necessary in order for BCI to deliver fluid and reliable control. Since Echo State Networks (ES...

Abstract We investigate the ability of an ensemble reservoir computing approach to predict long-term behaviour phase-space region in which motion charged particles hadron storage rings is bounded, so-called dynamic aperture. Currently, calculation stability performed through direct computer simulations, are resource- and time-intensive processes. Echo State Networks (ESN) a class recurrent neur...

Echo State Networks (ESNs) have tremendous potential on a variety of problems if successfully designed. The effects of varying two important ESN parameters, the spectral radius (alpha) and settling time (ST) are studied in this letter. Spectral radius of an ESN is the maximum of all eigenvalues of the reservoir weights whereas ST is measured by the number of iterations allowed in the reservoir ...

the application of neural networks to model a laboratory scale inverse fluidized bed reactor has been studied. a radial basis function neural network has been successfully employed for the modeling of the inverse fluidized bed reactor. in the proposed model, the trained neural network represents the kinetics of biological decomposition of organic matters in the reactor. the neural network has b...

in this paper, a novel hybrid model based on neural network and game theory is proposed to support the analyzers in oil market. in this model, first the neural network is utilized to learn the oil prices associated with opec production level and usa imports level. then the learned neural network is applied by a game model. finally the nash equilibrium points of the game present the optimum deci...

Social media makes fast inroads into corporate workplaces. Enterprise Social Networking (ESN) is associated with improved communication, information-sharing and has been argued to lead to more democratic communication patterns, whereby users increasingly derive authority from their contributions to the network rather than their position in the formal hierarchy. At the same time, this developmen...

The vanishing gradients problem inherent in Simple Recurrent Networks (SRN) trained with back-propagation, has led to a significant shift towards the use of Long Short-term Memory (LSTM) and Echo State Networks (ESN), which overcome this problem through either second order error-carousel schemes or different learning algorithms respectively. This paper re-opens the case for SRN-based approaches...

Variation among individuals is a prerequisite of evolution by natural selection. As such, identifying the origins of variation is a fundamental goal of biology. We investigated the link between gene interactions and variation in gene expression among individuals and species using the mammalian limb as a model system. We first built interaction networks for key genes regulating early (outgrowth;...

In recent years, with wide application of proton exchange membrane fuel cell (PEMFC) in vehicles and portable applications, researches regarding PEMFC lifetime behavior associated prognostic techniques receive more interest. this article, a least absolute shrinkage selection operator-echo state network (LASSO-ESN)-based strategy is proposed for the optimization input parameters long-term predic...