[HTML][HTML] Fault diagnosis of bearings based on deep separable convolutional neural network and spatial dropout
J Zhang, K Xiangwei, LI Xueyi, HU Zhiyong… - Chinese Journal of …, 2022 - Elsevier
Bearing pitting, one of the common faults in mechanical systems, is a research hotspot in
both academia and industry. Traditional fault diagnosis methods for bearings are based on …
both academia and industry. Traditional fault diagnosis methods for bearings are based on …
Partial discharge signal denoising with recursive continuous S-shaped algorithm in cables
Partial discharge (PD) detection plays a vital role in on-line condition monitoring of electrical
apparatus in the power systems. However, the noise of PD measurements significantly …
apparatus in the power systems. However, the noise of PD measurements significantly …
Implementation and test results of on‐channel repeater for ATSC 3.0 systems
S Ahn, S Kwon, HC Kwon, Y Kim, J Lee, YS Shin… - ETRI …, 2022 - Wiley Online Library
Despite the successful launch of Advanced Television Systems Committee (ATSC) 3.0
broadcasting worldwide, broadcasters are facing obstacles in constructing void‐less large …
broadcasting worldwide, broadcasters are facing obstacles in constructing void‐less large …
Projecting independent components of SPECT images for computer aided diagnosis of Alzheimer's disease
Finding sensitive and appropriate technologies for early detection of the Alzheimer's disease
(AD) are of fundamental importance to develop early treatments. Single Photon Emission …
(AD) are of fundamental importance to develop early treatments. Single Photon Emission …
Cascade–cascade least mean square (LMS) adaptive noise cancellation
AK Maurya - Circuits, Systems, and Signal Processing, 2018 - Springer
The paper presents a new model of noise cancellation using cascading of cascaded LMS
adaptive filters. The model has a combination of '2 N+ 1 2 N+ 1'LMS filters for N-stage of …
adaptive filters. The model has a combination of '2 N+ 1 2 N+ 1'LMS filters for N-stage of …
Variable learning adaptive gradient based control algorithm for voltage source converter in distributed generation
This study presents an adaptive control algorithm known as variable learning and adaptive
gradient based least mean square for improving the power quality features in standalone …
gradient based least mean square for improving the power quality features in standalone …
Robust Andrew's sine estimate adaptive filtering
The Andrew's sine function is a robust estimator, which has been used in outlier rejection
and robust statistics. However, the performance of such estimator does not receive attention …
and robust statistics. However, the performance of such estimator does not receive attention …
P300 brainwave extraction from EEG signals: An unsupervised approach
The P 300 is an endogenous event-related potential (ERP) that is naturally elicited by rare
and significant stimuli, arisen from the frontal, temporal and occipital lobe of the brain …
and significant stimuli, arisen from the frontal, temporal and occipital lobe of the brain …
Enhanced q-least Mean Square
In this work, a new class of stochastic gradient algorithm is developed based on q-calculus.
Unlike the existing q-LMS algorithm, the proposed approach fully utilizes the concept of q …
Unlike the existing q-LMS algorithm, the proposed approach fully utilizes the concept of q …
Modified model and algorithm of LMS adaptive filter for noise cancellation
The present research investigates the innovative concept of LMS adaptive noise
cancellation by means of a modified algorithm using an LMS adaptive filter along with their …
cancellation by means of a modified algorithm using an LMS adaptive filter along with their …