この商品を友人に教える:
Evolving Probabilistic Spiking Neural Networks: Modelling and Pattern Recognition of Spatio-temporal Brain Data (Eeg) Nuttapod Nuntalid
遠隔倉庫からの取り寄せ
Evolving Probabilistic Spiking Neural Networks: Modelling and Pattern Recognition of Spatio-temporal Brain Data (Eeg)
Nuttapod Nuntalid
The use of Electroencephalography (EEG) in Brain Computer Interface (BCI) domain presents a challenging problem due to presence of spatial and temporal aspects inherent in the EEG data. Many studies either transform the data into a temporal or spatial problem for analysis. This approach results in loss of significant information since these methods fail to consider the correlation present within the spatial and temporal aspect of the EEG data. However, Spiking Neural Network (SNN) naturally takes into consideration the correlation present within the spatio-temporal data. Hence by applying the proposed SNN based novel methods on EEG, the thesis provide improved analytic on EEG data. This book introduces novel methods and architectures for spatio-temporal data modelling and classification using SNN. More specifically, SNN is used for analysis and classification of spatiotemporal EEG data.
| メディア | 書籍 Paperback Book (ソフトカバーで背表紙を接着した本) |
| リリース済み | 2013年7月17日 |
| ISBN13 | 9783659430800 |
| 出版社 | LAP LAMBERT Academic Publishing |
| ページ数 | 256 |
| 寸法 | 150 × 15 × 225 mm · 381 g |
| 言語 | 英語 |