Narayan P. Subramaniyam
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Characterization of dynamical systems under noise using recurrence networks: Application to simulated and EEG data
NP Subramaniyam, J Hyttinen
Physics Letters A 378 (46), 3464-3474, 2014
Dynamics of intracranial electroencephalographic recordings from epilepsy patients using univariate and bivariate recurrence networks
NP Subramaniyam, J Hyttinen
Physical Review E 91 (2), 022927, 2015
Analysis of nonlinear dynamics of healthy and epileptic EEG signals using recurrence based complex network approach
NP Subramaniyam, J Hyttinen
2013 6th International IEEE/EMBS Conference on Neural Engineering (NER), 605-608, 2013
Fusionsense: Emotion classification using feature fusion of multimodal data and deep learning in a brain-inspired spiking neural network
C Tan, G Ceballos, N Kasabov, N Puthanmadam Subramaniyam
Sensors 20 (18), 5328, 2020
Signatures of chaotic and stochastic dynamics uncovered with ϵ-recurrence networks
NP Subramaniyam, JF Donges, J Hyttinen
Proceedings of the Royal Society A: Mathematical, Physical and Engineering …, 2015
Non-linear dynamical analysis of resting tremor for demand-driven deep brain stimulation
C Camara, NP Subramaniyam, K Warwick, L Parkkonen, T Aziz, E Pereda
Sensors 19 (11), 2507, 2019
Waveform complexity: A new metric for EEG analysis
D Parameshwaran, NP Subramaniyam, TC Thiagarajan
Journal of neuroscience methods 325, 108313, 2019
Cortical potential imaging using L-curve and GCV method to choose the regularisation parameter
NP Subramaniyam, ORM Väisänen, KE Wendel, JAV Malmivuo
Nonlinear Biomedical Physics 4 (1), 1-11, 2010
Tracking of dynamic functional connectivity from MEG data with Kalman filtering
F Tronarp, NP Subramaniyam, S Särkkä, L Parkkonen
2018 40th Annual International Conference of the IEEE Engineering in …, 2018
Recurrence network analysis of wide band oscillations of local field potentials from the primary motor cortex reveals rich dynamics
NP Subramaniyam, J Hyttinen, NG Hatsopoulos, K Takahashi
2015 7th International IEEE/EMBS Conference on Neural Engineering (NER), 960-963, 2015
Investigating the measurement capability of densely-distributed subdermal EEG electrodes
NP Subramaniyam, K Wendel, A Joutsen, J Hyttinen
2011 8th International Symposium on Noninvasive Functional Source Imaging of …, 2011
Measuring entropy in the eeg
NP Subramaniyam
Sapien Labs 5, 2018
Causal coupling inference from multivariate time series based on ordinal partition transition networks
NP Subramaniyam, RV Donner, D Caron, G Panuccio, J Hyttinen
Nonlinear Dynamics 105 (1), 555-578, 2021
Expectation–maximization algorithm with a nonlinear Kalman smoother for MEG/EEG connectivity estimation
NP Subramaniyam, F Tronarp, S Särkkä, L Parkkonen
EMBEC & NBC 2017, 763-766, 2017
Evaluating the electrode measurement sensitivity of subdermal electroencephalography electrodes
MR Mendes, NP Subramaniyam, K Wendel-Mitoraj
2015 7th International IEEE/EMBS Conference on Neural Engineering (NER …, 2015
Source localization based on ictal electroencephalographic recordings
NP Subramaniyam, J Peltola, J Tanskanen, K Wendel-Mitoraj, J Hyttinen, ...
International Symposium on Biomedical Engineering and Medical Physics, 10-12 …, 2013
Electrical fields of the sleep-related slow-wave EEG patterns in anaesthesia
V Jantti, P Kauppinen, O Vaisanen, K Wendel, N Subramaniyam, ...
British Journal of Anaesthesia 108 (2), 343P-344P, 2012
Recurrence network analysis of EEG signals: A Geometric Approach
NP Subramaniyam
Tampere University of Technology, 2016
Electroencephalographic signals during anesthesia recorded from surface and depth electrodes
V Jäntti, T Ylinen, NP Subramaniyam, K Kamata, A Yli-Hankala, ...
International Journal of Radiation Biology 94 (10), 934-943, 2018
Abstracts of Presentations at the International Conference on Basic and Clinical Multimodal Imaging (BaCI), a Joint Conference of the International Society for Neuroimaging in …
BJ He, G Nolte, K Nagata, D Takano, T Yamazaki, Y Fujimaki, T Maeda, ...
Clinical EEG and neuroscience, 2013
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