Power System Parameters Forecasting Using Hilbert-Huang Transform and Machine Learning
A novel hybrid data-driven approach is developed for forecasting power system parameters with the goal of increasing the efficiency of short-term forecasting studies for non-stationary time-series. The proposed approach is based on mode decomposition and
V.G. Kurbatsky +5 more
doaj
Multicomponent Chirp-like Jammer Excision in DSSS Communication Systems Using Hilbert-Huang Hough Transform [PDF]
A novel and efficient approach for multicomponent chirp-like jammer excision in direct sequence spread spectrum (DSSS) communication systems using Hilbert-Huang Hough (HH-H) transform is proposed, which is the generalization of marginal Hilbert spectrum.
Ye, Yuan, Wenbo, Mei
core +1 more source
Motion Capture Data Analysis in the Instantaneous Frequency-Domain Using Hilbert-Huang Transform. [PDF]
Dong R, Cai D, Ikuno S.
europepmc +1 more source
Hilbert-Huang transform based pupil changes analysis for concentration assessment in skilled mowing. [PDF]
Wu B +6 more
europepmc +1 more source
Chatter Detection in Milling of Carbon Fiber-Reinforced Composites by Improved Hilbert-Huang Transform and Recurrence Quantification Analysis. [PDF]
Rusinek R, Lajmert P.
europepmc +1 more source
Hilbert-Huang Transform Embedded Self-Attention Neural Network for EEG-based major depressive disorder vs. healthy controls classification. [PDF]
Chen J, Tian K, Ye Y, Liu J.
europepmc +1 more source
Correction: Drilling-vibration response characteristics of rocks based on Hilbert–Huang transform
Xinxin Fang +7 more
doaj +1 more source
Time-Frequency Analysis of Particulate Matter (PM10) Concentration in Dry Bulk Ports Using the Hilbert-Huang Transform. [PDF]
Feng X +5 more
europepmc +1 more source
High resistance fault detection in DC microgrid using Hilbert Huang transform and vector-based ensemble optimized LSTM networks. [PDF]
Kumar HKP +4 more
europepmc +1 more source
Electromyography signal based hand gesture classification system using Hilbert Huang transform and deep neural networks. [PDF]
S MV, A HL, Fouad Y, Soudagar MEM.
europepmc +1 more source

