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eess.SP2025
Intrinsic frequency distribution characterises neural dynamics
Ryohei Fukuma, Yoshinobu Kawahara, Okito Yamashita +3
Decomposing multivariate time series with certain basic dynamics is crucial for understanding, predicting and controlling nonlinear spatiotemporally dynamic systems such as the bra…
eess.SP2023
Fast, accurate, and interpretable decoding of electrocorticographic signals using dynamic mode decomposition
Ryohei Fukuma, Kei Majima, Yoshinobu Kawahara +4
Dynamic mode (DM) decomposition decomposes spatiotemporal signals into basic oscillatory components (DMs). DMs can improve the accuracy of neural decoding when used with the nonlin…