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Microelectrode Signals Segmentation Using Stationary Wavelet Transform.

, , and . BMEI (2), page 450-454. IEEE Computer Society, (2008)978-0-7695-3118-2.

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Fast Kernel Approximations for Latent Force Models and Convolved Multiple-Output Gaussian processes., and . UAI, page 835-844. AUAI Press, (2018)Impulse Response Estimation of Linear Time-Invariant Systems Using Convolved Gaussian Processes and Laguerre Functions., and . CIARP, volume 10657 of Lecture Notes in Computer Science, page 281-288. Springer, (2017)Non-linear process convolutions for multi-output Gaussian processes., , and . CoRR, (2018)Optimal sampling frequency in wavelet-based signal feature extraction using particle swarm optimization., , and . EMBC, page 993-996. IEEE, (2013)Non-linear process convolutions for multi-output Gaussian processes., , and . AISTATS, volume 89 of Proceedings of Machine Learning Research, page 1969-1977. PMLR, (2019)Microelectrode Signals Segmentation Using Stationary Wavelet Transform., , and . BMEI (2), page 450-454. IEEE Computer Society, (2008)978-0-7695-3118-2.Simplified Mathematical Model for Calculating the Oxygen Excess Ratio of a PEM Fuel Cell System in Real-Time Applications., , , , , , and . IEEE Trans. Industrial Electronics, 61 (6): 2816-2825 (2014)Indian Buffet Process for Model Selection in Latent Force Models., , and . CIARP, volume 9423 of Lecture Notes in Computer Science, page 635-642. Springer, (2015)Non-linear System Identification by a Fuzzy Takagi-Sugeno System Approach based on Reusable Fuzzified Inputs., and . IJCCI, page 424-428. SciTePress, (2012)