Brain Computer Interfaces: A Recurrent Neural Network Approach

被引：0

作者：

Oliver, Gareth ^{[1
]}

Gedeon, Tom ^{[1
]}

机构：

[1] Australian Natl Univ, Canberra, ACT 0200, Australia

来源：

NEURAL INFORMATION PROCESSING: MODELS AND APPLICATIONS, PT II | 2010年 / 6444卷

关键词：

BCI; RNN; CasPer; Echostate Network;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper explores the use of recurrent neural networks in the field of Brain Computer Interfaces(BCI). In particular it looks at a recurrent neural network, an echostate network and a CasPer neural network and attempts to use them to classify data from BCI competition Ills dataset IVa. In addition it proposes a new method. EchoCasPer, which uses the Cas Per training scheme in a recurrent neural network. The results showed that temporal information existed within the BCI data to be made use of, but further pre-processing and parameter exploration was needed to reach competitive classification rates.

引用

页码：66 / 73

页数：8

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