• No se han encontrado resultados

BRAIN COMPUTER INTERFACE - Application of an Adaptive Bi-stage Classifier based on RBF-HMM

N/A
N/A
Protected

Academic year: 2020

Share "BRAIN COMPUTER INTERFACE - Application of an Adaptive Bi-stage Classifier based on RBF-HMM"

Copied!
8
0
0

Texto completo

Loading

Figure

Figure 1: Block diagram of a BCI device.
Figure 3: Electrode placement.
Figure 5: Block diagram for the preprocessing phase.
Figure 7: Architecture of the RBF neural network.
+2

Referencias

Documento similar

In the preparation of this report, the Venice Commission has relied on the comments of its rapporteurs; its recently adopted Report on Respect for Democracy, Human Rights and the Rule

For example, the conceptual representations proposed are in the form of computer-implemented ontologies. No mention is made of prototypes, ideal- ized cognitive models or

This is why there are many business models and all of them are important to achieve success across different companies, as long as the correct choice is made in

Train: All the models (T-HMM, adaptive T- HMM, Naive Bayes, k-NN and a SVM) are trained with the training corpus created in the preprocessing step.. Learn: In the case of the

The application of cultural models such as the Health Traditions Model, can be an interesting tool for health professionals to verify the role that culture has

Method: This article aims to bring some order to the polysemy and synonymy of the terms that are often used in the production of graphic representations and to

A stochastic model based on Markov Chains is presented for predicting the time evolution of the pit depth distributions, as manifestation of the corrosion

As far as we know, the role of SAs in the survival of the company is still in an incipient stage, since there are few studies available based on qualitative data (Lukas et al. Our