Identification of epilepsy from intracranial EEG signals by using different neural network models
文献类型：期刊论文
| 作者 | Gong C(龚晨)2,3 ; Zhang XX(张肖雄)1; Niu YY(牛云云)3
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| 刊名 | Computational Biology and Chemistry
 |
| 出版日期 | 2020 |
| 页码 | 107310 |
| 英文摘要 | In this work, a framework is provided for identifying intracranialf propagation and feedback neural networks. The performance of 5 different data sets combination classififications is studied using the probabilistic neural network (PNN), learning vector quantization neural network (LVQ) and Elman neural network (ENN). Different feature combinations serve as the input vectors of the classififiers to obtain the best outcomes. It has been found that PNN has less running time and provides better classification accuracy (CA) than ENN and LVQ
classifers for all 5 classification problems. It is worth noticing that the CA for the C-D classification task, which shows the status of pre-ictal versus post-ictal, has been greatly improved, and reached 83.13%. Hence, the epilepsy iEEG signals pattern recognition based on DWT statistical features using the PNN classifier is more suitable for forming a reliable, automatic classification system in order to assist doctors in diagnosis. |
| 语种 | 英语 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/52200]  |
| 专题 | 自动化研究所_复杂系统管理与控制国家重点实验室_机器人应用与理论组 |
| 作者单位 | 1.School of Chemical Engineering and Technology, Tianjin University, Tianjin 300350, China 2.Institute of Automation, Chinese Academy of Sciences 3.School of Information Engineering, China University of Geosciences in Beijing, Beijing 100083, China |
| 推荐引用方式 GB/T 7714 | Gong C,Zhang XX,Niu YY. Identification of epilepsy from intracranial EEG signals by using different neural network models[J]. Computational Biology and Chemistry,2020:107310. |
| APA | Gong C,Zhang XX,&Niu YY.(2020).Identification of epilepsy from intracranial EEG signals by using different neural network models.Computational Biology and Chemistry,107310. |
| MLA | Gong C,et al."Identification of epilepsy from intracranial EEG signals by using different neural network models".Computational Biology and Chemistry (2020):107310. |
入库方式： OAI收割
来源：自动化研究所
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