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Multi-subject Resting-State fMRI Data Analysis via Generalized Canonical Correlation Analysis.

, , , , and . EUSIPCO, page 1040-1044. IEEE, (2020)

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Numerical stability issues of the conventional recursive least squares algorithm., and . ICASSP, page 1409-1412. IEEE, (1998)Performance analysis and comparison of blind to non-blind least-squares equalization with respect to effective channel overmodeling., and . Signal Process., 82 (9): 1233-1253 (2002)On the Performance of the Mismatched MMSE and the LS Linear Equalizers., and . IEEE Trans. Signal Process., 55 (7-1): 3302-3311 (2007)Nesterov-Based Alternating Optimization for Nonnegative Tensor Factorization: Algorithm and Parallel Implementation., , , , and . IEEE Trans. Signal Process., 66 (4): 944-953 (2018)Design of LDPC Codes for the Unequal Power Two-User Gaussian Multiple Access Channel., and . IEEE Wirel. Commun. Lett., 7 (5): 868-871 (2018)Single-carrier systems with MMSE linear equalizers: Performance degradation due to channel and CFO estimation errors., and . ICASSP, page 3384-3387. IEEE, (2011)Multisubject Task-Related fMRI Data Processing via a Two-Stage Generalized Canonical Correlation Analysis., , , , and . IEEE Trans. Image Process., (2022)A Flexible and Efficient Algorithmic Framework for Constrained Matrix and Tensor Factorization., , and . IEEE Trans. Signal Process., 64 (19): 5052-5065 (2016)Parallel algorithms for large scale constrained tensor decomposition., and . ICASSP, page 2459-2463. IEEE, (2015)On the robustness of the linear prediction method for blind channel identification with respect to effective channel undermodeling/overmodeling., , and . IEEE Trans. Signal Process., 48 (5): 1477-1481 (2000)