Publications

Journal

Xiulin Wang, Wenya Liu, Jing Xu et al. Shared and Unshared Feature Extraction in Major Depression During Music Listening Using Constrained Tensor Factorization. Frontiers in Human Neuroscience (2021): 759. [link]
Wenya Liu, Xinlin Wang, Jing Xu et al.Identifying Oscillatory Hyperconnectivity and Hypoconnectivity Networks in Major Depression Using Coupled Tensor Decomposition. IEEE Transactions on Neural Systems and Rehabilitation Engineering 29(2021), 1895–1904. [link]
Xiaoshuang Wang, Xiulin Wang, Wenya Liu et al. One dimensional convolutional neural networks for seizure onset detection using long-term scalp and intracranial EEG. Neurocomputing 459 (2021): 212-222. [link]
Xiulin Wang, Wenya Liu, Tapani Ristaniemi and Fengyu Cong. Group analysis of ongoing EEG data based on fast double-coupled nonnegative tensor decomposition. Journal of neuroscience methods 330 (2020): 108502. [link]
Xiaofeng Gong, Xiulin Wang, and Qiuhua Lin. Generalized non-orthogonal joint diagonalization with LU decomposition and successive rotations. IEEE Transactions on Signal Processing 63, no. 5 (2015): 1322-1334. [link]

Wenya Liu, Xiulin Wang, Fengyu Cong, and Timo Hämäläinen. Alpha Band Dysconnectivity Networks in Major Depression during Resting State. 29th European Signal Processing Conference (EUSIPCO), 2021. [link]
Xiulin Wang, Wenya Liu, Fengyu Cong, and Tapani Ristaniemi. Group Nonnegative Matrix Factorization with Sparse Regularization in Multi-set Data. 28th European Signal Processing Conference (EUSIPCO), 2021. Accepted as poster. [link]
Wenya Liu, Xiulin Wang, Tapani Ristaniemi, and Fengyu Cong.Identifying Task-Based Dynamic Functional Connectivity Using Tensor Decomposition. International Conference on Neural Information Processing(ICNIP), 2020. [link]
Xiulin Wang, Chi Zhang, Tapani Ristaniemi, Fengyu Cong. Generalization of Linked Canonical Polyadic Tensor Decomposition for Group Analysis. International Symposium on Neural Networks (ISNN), 2019. [link]
xiulin Wang, Tapani Ristaniemi, Fengyu Cong. Fast Implementation of Double-coupled Nonnegative Canonical Polyadic Decomposition. International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2019. Accepted as poster. [link]
Xiulin Wang, Xiaofeng Gong, Qiuhua Lin. A Study on Parallelization of Successive Rotation Based Joint Diagonalization. International Conference on Digital Signal Processing (DSP), 2014. Accepted as presentation. [link]

GNJD_Software_Package:
Authors: Xiaofeng Gong, Xiulin Wang, Qiuhua Lin
Generalized Non-orthogonal Joint Diagonalization (GNJD) is an algorithm to simultaneously perform multiple asymmetric NJD upon multiple sets of target matrices with mutually linked loading matrices. It is a promising method to multiset data analysis problems such as joint blind source separation (J-BSS) and multiset data fusion. This software package provides source programs of GNJD to enable reproduction of the results in the published paper. We provide the routines of all the 5 experiments in the paper for our algorithms (GNJD and 2 other earlier related works). Results for other competitors, however, are not included to avoid copyright conflicts. Data and some routines for the last 2 experiments are obtained from internationally published benchmarks. We include them in the package to enable successful execution for these examples. [User Guide] [Download]