Παρακολούθηση
Geir Kulia
Geir Kulia
Signal Analysis Lab
Η διεύθυνση ηλεκτρονικού ταχυδρομείου έχει επαληθευτεί στον τομέα ieee.org - Αρχική σελίδα
Τίτλος
Παρατίθεται από
Παρατίθεται από
Έτος
Real-time passive control of wave energy converters using the Hilbert-Huang transform
PB Garcia-Rosa, G Kulia, JV Ringwood, M Molinas
IFAC-PapersOnLine 50 (1), 14705-14710, 2017
392017
Towards a Real-time Measurement Platform for Microgrids in Isolated Communities
G Kulia, M Molinas, L Lundheim, BB Larsen
Procedia Engineering, Elsevier 159 (1877-7058 © 2016), 94-103, 2016
182016
Understanding instantaneous frequency detection: A discussion of Hilbert-Huang Transform versus Wavelet Transform
M Bueno-López, M Molinas, G Kulia
International Work-Conference on Time Series Analysis-ITISE 1, 474-486, 2017
172017
Prediction of dynamic mooring responses of a floating wind turbine using an artificial neural network
FA Bjørni, S Lien, TA Midtgarden, G Kulia, A Verma, Z Jiang
IOP Conference Series: Materials Science and Engineering 1201 (1), 012023, 2021
162021
Tool for detecting waveform distortions in inverter-based Microgrids: a validation study
G Kulia, M Molinas, L Lundheim
2016 IEEE Global Humanitarian Technology Conference (GHTC 2016), 2016
62016
Investigation of distortions in microgrids
G Kulia
NTNU, 2016
42016
Simple model for understanding harmonics propagation in single-phase microgrids
G Kulia, M Molinas, LM Lundheim, OB Fosso
2017 6th International Conference on Clean Electrical Power (ICCEP), 354-358, 2017
32017
Impact of time varying angular frequency on the separation of instantaneous power components in stand-alone power systems
B Hillenbrand, G Kulia, M Molinas
2017 6th International Conference on Clean Electrical Power (ICCEP), 347-353, 2017
32017
Instantaneous Frequencies of Continuous Blood Pressure a Comparison of the Power Spectrum, the Continuous Wavelet Transform and the Hilbert–Huang Transform
K Knai, G Kulia, M Molinas, NK Skjaervold
Advances in Data Science and Adaptive Analysis 9 (04), 1750009, 2017
22017
On wind Turbine failure detection from measurements of phase currents: a permutation entropy approach
SK Ram, G Kulia, M Molinas
arXiv preprint arXiv:1601.05387, 2016
22016
Analysis of healthy and failed wind turbine electrical data: apermutation entropy approach
SK Ram, G Kulia, M Molinas
Department of Engineering Cybernetics, Internal publications, NTNU, 2016
22016
Instantaneous Frequency in Electric Power Systems
M Molinas, G Kulia, OB Fosso
NTNU, 2016
12016
On wind Turbine failure detection from measurements of phase currents: a permutation entropy approach
MM Molinas Cabrera, G Kulia, S Kumar Ram
Cornell University Library, arXiv. org, 2016
2016
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