KAMBLE K, SENGUPTA J. A Comprehensive Survey on Emotion Recognition Based on Electroencephalograph (EEG) Signals [J]. Multimedia Tools and Applications, 2023, 82(18): 27269-27304. doi: 10.1007/s11042-023-14489-9
KUMAR G S, SAMPATHILA N, MARTIS R J. Classification of Human Emotional States Based on Valence-Arousal Scale Using Electroencephalogram [J]. Journal of Medical Signals & Sensors, 2023, 13(2): 173-182.
MALKAWI M, MURAD O. Artificial Neuro Fuzzy Logic System for Detecting Human Emotions [J]. Human-Centric Computing and Information Sciences, 2013, 3(1): 3. doi: 10.1186/2192-1962-3-3
ALRUWAILI M, ALRUWAILI R, KUMAR U A, et al. Human Emotion Recognition Based on Brain Signal Analysis Using Fuzzy Neural Network [J]. Soft Computing, 2023: 1-15.
LI Y X, FU Z Z, HE X R, et al. An Optimized Multi-Label TSK Fuzzy System for Emotion Recognition of Multimodal Physiological Signals [C] //2022 IEEE International Conference on Cyborg and Bionic Systems (CBS), March 24-26, 2023, Wuhan, China. IEEE, 2023: 362-367.
DHARA T, SINGH P K, MAHMUD M. A Fuzzy Ensemble-Based Deep Learning Model for EEG-Based Emotion Recognition [J]. Cognitive Computation, 2024, 16(3): 1364-1378. doi: 10.1007/s12559-023-10171-2
HASANZADEH F, ANNABESTANI M, MOGHIMI S. Continuous Emotion Recognition during Music Listening Using EEG Signals: A Fuzzy Parallel Cascades Model [J]. Applied Soft Computing, 2021, 101: 107028. doi: 10.1016/j.asoc.2020.107028
GU X Q, WANG Y T, WANG M X, et al. A Multi-View Semi-Supervised Takagi-Sugeno-Kang Fuzzy System for EEG Emotion Classification [J]. International Journal of Fuzzy Systems, 2024, 26(4): 1285-1299. doi: 10.1007/s40815-023-01666-z
AHMADZADEH NOBARI AZAR N, CAVUS N, ESMAILI P, et al. Detecting Emotions through EEG Signals Based on Modified Convolutional Fuzzy Neural Network [J]. Scientific Reports, 2024, 14: 10371. doi: 10.1038/s41598-024-60977-9
ZHANG Y C, YAN G H, CHANG W W, et al. EEG-Based Multi-Frequency Band Functional Connectivity Analysis and the Application of Spatio-Temporal Features in Emotion Recognition [J]. Biomedical Signal Processing and Control, 2023, 79: 104157. doi: 10.1016/j.bspc.2022.104157
梁花, 李洋, 雷娟, 等. 基于模糊证据理论的物联网节点评估方法研究[J]. 西南师范大学学报(自然科学版), 2022, 47(3): 111-124.
刘玉军, 姚合军. 基于网络的T-S模糊系统的有限时间控制[J]. 西南大学学报(自然科学版), 2022, 44(9): 187-196. doi: 10.13718/j.cnki.xdzk.2022.09.019
张红英, 董珂臻. 稀疏统计学习及其最新研究进展综述[J]. 西南师范大学学报(自然科学版), 2023, 48(4): 1-12.
WU Y Z, CHEN Y K, YIN Z S, et al. A Survey on Graph Embedding Techniques for Biomedical Data: Methods and Applications [J]. Information Fusion, 2023, 100: 101909. doi: 10.1016/j.inffus.2023.101909
QI L, HUO J, FAN X C, et al. Unsupervised Joint Subspace and Dictionary Learning for Enhanced Cross-Domain Person Re-Identification [J]. IEEE Journal of Selected Topics in Signal Processing, 2018, 12(6): 1263-1275. doi: 10.1109/JSTSP.2018.2877475
DEAP: A Dataset for Emotion Analysis Using EEG, Physiological and Video Signals [DB/OL]. [2024-01-29]. http://www.eecs.qmul.ac.uk/mmv/datasets/deap/readme.html.
PEREIRA E T, GOMES H M, VELOSO L R, et al. Empirical Evidence Relating EEG Signal Duration to Emotion Classification Performance [J]. IEEE Transactions on Affective Computing, 2021, 12(1): 154-164. doi: 10.1109/TAFFC.2018.2854168
UYANIK H, OZCELIK S T A, DURANAY Z B, et al. Use of Differential Entropy for Automated Emotion Recognition in a Virtual Reality Environment with EEG Signals [J]. Diagnostics, 2022, 12(10): 2508. doi: 10.3390/diagnostics12102508
JUANG C F, HSIEH C D. A Fuzzy System Constructed by Rule Generation and Iterative Linear SVR for Antecedent and Consequent Parameter Optimization [J]. IEEE Transactions on Fuzzy Systems, 2012, 20(2): 372-384. doi: 10.1109/TFUZZ.2011.2174997
LIU H, ZHANG L. Fuzzy Rule-Based Systems for Recognition-Intensive Classification in Granular Computing Context [J]. Granular Computing, 2018, 3(4): 355-365. doi: 10.1007/s41066-018-0076-7
AYRES A O C, VON ZUBEN F J. Multitask Learning Applied to Evolving Fuzzy-Rule-Based Predictors [J]. Evolving Systems, 2021, 12(2): 407-422. doi: 10.1007/s12530-019-09300-w
HUANG C Q, CHUNG F L, WANG S T. Multi-View L2-SVM and Its Multi-View Core Vector Machine [J]. Neural Networks, 2016, 75: 110-125. doi: 10.1016/j.neunet.2015.12.004
YANG M L, DENG C, NIE F P. Adaptive-Weighting Discriminative Regression for Multi-View Classification [J]. Pattern Recognition, 2019, 88: 236-245. doi: 10.1016/j.patcog.2018.11.015
LI Y R, QIAN P J, WANG S H, et al. Novel Multi-View Takagi-Sugeno-Kang Fuzzy System for Epilepsy EEG Detection [J]. Journal of Ambient Intelligence and Humanized Computing, 2023, 14(5): 5625-5645. doi: 10.1007/s12652-021-03189-7