The depression treatment screening system can predict the efficacy of rapid antidepressant agents.
2423-2427.View/Download from: Publisher's site. 1, pp.
Cao, ZH, Ko, LW, Lai, KL, Huang, SB, Wang, SJ & Lin, CT 2015, 'Classification of migraine stages based on resting-state EEG power', Proceedings of the International Joint Conference on Neural Networks, IEEE International Joint Conference on Neural Networks, IEEE, Killarney, Ireland.View/Download from: Publisher's site.
Two recent trends in research in the computational and artificial intelligence community, big data and deep learning, are expected to impact the direction and development of BCIs. Compared with the state-of-art baselines, the proposed method is able to achieve favorable and stable results in multi-label classification and link prediction tasks.
Based on the simulation results, it can verify the rationality and superiority of our proposed evaluation index. For example, if the network operator's permission is illegally obtained by a hacker, he/she can control the entry of the SDN network.
1-12.View/Download from: Publisher's site, Cheng, C, Xiao, F & Cao, Z 2019, 'A New Distance for Intuitionistic Fuzzy Sets Based on Similarity Matrix', IEEE ACCESS, vol. This algorithm is a purely local algorithm and can be applied directly to higher-order graphs without conversion to a weighted graph, thus avoiding distortion of the transform. Cao, Z, Chang, YC, Prasad, M, Tanveer, M & Lin, CT 2019, 'Tensor decomposition for EEG signals retrieval', Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics, IEEE International Conference on Systems, Man and Cybernetics, IEEE, Bari, Italy, pp. Taking linear weight greedy streaming algorithm as an example, the experimental results on 19 real-world graphs show that the average partitioning time of the new method is 4.9 times faster than that of the original method, which proves the effectiveness and superiority of the cache structure mentioned in this paper. 6, no. IEEE The main challenge of attribute reduction in large data applications is to develop a new algorithm to deal with large, noisy, and uncertain large data linking multiple relevant data sources, structured or unstructured. Positions. 7, no. © 2014 IEEE. 1, pp. Prior studies have proposed methods to recover multi-channel electroencephalography (EEG) signal ensembles from their partially sampled entries. Furthermore, it can be well applied to clearly identify different longitudinal surfaces of infant cerebrum regions, which indicates its great potential for brain disorder prediction based on fMRI. Our proposed method represents the first attempt to use the Inherent FuzzyEn algorithm to increase the reliability of complexity evaluation in realistic EEG applications. We recorded the EEG signals of several subjects under resting condition, and the EEG complexity was evaluated using approximate entropy, sample entropy, FuzzyEn, and Inherent FuzzyEn, respectively.
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