Fuzzy entropy and its application for enhanced subspace filtering
Fuzzy entropy (FuzzyEn), which employs the fuzzy probability to characterize the similarity
between vectors, is a robust nonlinear statistic to quantify the complexity or regularity of …
between vectors, is a robust nonlinear statistic to quantify the complexity or regularity of …
[HTML][HTML] Laboratory study of wave-induced flexural motion of ice floes
H Li, ED Gedikli, R Lubbad - Cold Regions Science and Technology, 2021 - Elsevier
Wave-ice interactions involve complex physical processes. Well-designed laboratory
investigations are indispensable for studying these processes. In the present study …
investigations are indispensable for studying these processes. In the present study …
A grid-based nonlinear approach to noise reduction and deconvolution for coupled systems
To varying degrees, all experimental measurements are corrupted by real-world noise
sources including electronic noise in the acquisition system, far-field perturbations in the …
sources including electronic noise in the acquisition system, far-field perturbations in the …
Improvements to local projective noise reduction through higher order and multiscale refinements
The broad spectrum characteristic of signals from nonlinear systems obstructs noise
reduction techniques developed for linear systems. Local projection was developed to …
reduction techniques developed for linear systems. Local projection was developed to …
[HTML][HTML] Clustering based multiple state–space projections
Abstract The method of Nonlinear State–Space Projections (NSSP) is very effective in
suppression of white Gaussian noise; however, in colored noise environment its operation is …
suppression of white Gaussian noise; however, in colored noise environment its operation is …
Estimation of biophysical parameters in a neuron model under random fluctuations
RK Upadhyay, C Paul, A Mondal… - Applied Mathematics and …, 2018 - Elsevier
In this paper, an attempt has been made to estimate the biophysical parameters in an
improved version of Morris–Lecar (M–L) neuron model in a noisy environment. To observe …
improved version of Morris–Lecar (M–L) neuron model in a noisy environment. To observe …
Fault classification of rotary machinery based on smooth local subspace projection method and permutation entropy
L Xiao, Y Lv, G Fu - Applied Sciences, 2019 - mdpi.com
Collected mechanical signals usually contain a number of noises, resulting in erroneous
judgments of mechanical condition diagnosis. The mechanical signals, which are nonlinear …
judgments of mechanical condition diagnosis. The mechanical signals, which are nonlinear …
On clustering based nonlinear projective filtering of biomedical signals
We propose to modify the method of nonlinear state-space projections (NSSP) by
application of the technique of k-means clustering. NSSP performs reconstruction of the …
application of the technique of k-means clustering. NSSP performs reconstruction of the …
Phase Space Smooth Mode Decomposition for Bearing Fault Diagnosis
In the field of rolling bearing fault diagnosis, significant attention has been devoted to
modeling and identifying parameters for the vibration dynamic system. Aiming at the …
modeling and identifying parameters for the vibration dynamic system. Aiming at the …
[HTML][HTML] Toward a unified interpretation of the “proper”/“smooth” orthogonal decompositions and “state variable”/“dynamic mode” decompositions with application to …
AA Khan, J Kuehl, D Chelidze - AIP Advances, 2020 - pubs.aip.org
A common interpretation is presented for four powerful modal decomposition
techniques:“proper orthogonal decomposition,”“smooth orthogonal decomposition,”“state …
techniques:“proper orthogonal decomposition,”“smooth orthogonal decomposition,”“state …