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
收藏
页码：66 / 73
页数：8
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