Adaptive filtering for microelectromechanical inertial sensors using empirical mode decomposition, Hausdorff distance and fractional Gaussian noise modeling
Authors:
- João CampelloJCJoão Campello
- Daniel SantosDSDaniel Santos
- Marcos PintoMPMarcos Pinto
- 6 June 2024
- journal article
- research article
- Published by Elsevier in Digital Signal Processing
- Vol. 153
Abstract
No abstract availableKeywords
This publication has 22 references indexed in Scilit:
- Denoising for satellite laser altimetry full-waveform data based on EMD-Hurst analysisInternational Journal of Digital Earth, 2019
- Intelligent GNSS/INS integrated navigation system for a commercial UAV flight control systemAerospace Science and Technology, 2018
- An efficient ECG denoising methodology using empirical mode decomposition and adaptive switching mean filterBiomedical Signal Processing and Control, 2018
- Hybrid methods for MEMS gyro signal noise reduction with fast convergence rate and small steady-state errorSensors and Actuators A: Physical, 2018
- Variational mode decomposition denoising combined with the Hausdorff distanceReview of Scientific Instruments, 2017
- An EMD threshold de-noising method for inertial sensorsMeasurement, 2014
- A correlated empirical mode decomposition method for partial discharge signal denoisingMeasurement Science and Technology, 2010
- EMD based multi-scale model for high resolution image fusionGeo-spatial Information Science, 2008
- Application of EMD method and Hilbert spectrum to the fault diagnosis of roller bearingsMechanical Systems and Signal Processing, 2005
- Ideal spatial adaptation by wavelet shrinkageBiometrika, 1994