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Hybrid compression scheme based on VMD optimization algorithm application to mechanical equipment monitoring
The traditional variational mode decomposition (VMD) algorithm causes under-decomposition and over-decomposition problems when performing signal...
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VMD based wavelet hybrid denoising and improved FBCCA algorithm: a new technique for wearable SSVEP recognition
The brain-computer interface based on steady-state visual evoked potential (SSVEP) has gained increasing attention due to its non-invasiveness, low...
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VMD-AC-LSTM: An Accurate Prediction Method for Solar Irradiance
Currently, solar power has become one of the most promising new power generation methods. But electricity cannot be stored directly and solar power...
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A-VMD: Adaptive Variational Mode Decomposition Scheme for Noise Reduction in Sensor-Cloud
Digital signal processing is critical during the use of sensor-clouds, and the data information acquired by sensors is inevitably noisy. The...
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VMD-based ECG signal watermarking using image fusion: a robust and versatile approach for secure telemedical services
Presently, telemedical services in different forms are being exploited for the distribution of medical amenities. Security necessities including...
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Epileptic EEG signal classification using an improved VMD-based convolutional stacked autoencoder
Numerous techniques have been explored so far for epileptic electroencephalograph (EEG) signal detection and classification. Deep learning-based...
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2D-VMD Embedded Fusion of Infrared Polarization and Intensity Images Using Muitiple-Algorithms Based on Their Complementary Relation
AbstractThe keys to multiple-algorithm fusion methods are the selection of the fusion algorithms and sequence of combination. In this paper, a new...
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Ultra-short-Term Load Forecasting Model Based on VMD and TGCN-GRU
Load forecasting is to use historical load information to estimate the load demand for a period of time in the future. At present, mode decomposition...
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Fault diagnosis method of rolling bearings based on VMD and MDSVM
Rolling bearings are one of the most vulnerable parts in rotating machines. This paper presents a novel approach to identify the rolling bearings...
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Adaptive diagnosis of DC motors using R-WDCNN classifiers based on VMD-SVD
Traditional fault diagnosis methods of DC (direct current) motors require high expertise and human labor. However, the other disadvantages of these...
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A fault diagnosis method of rolling bearing based on VMD Tsallis entropy and FCM clustering
A new fault diagnosis method of rolling bearings was presented based on variational mode decomposition (VMD), Tsallis entropy and Fuzzy C-means...
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Combined VMD-GSO Based Points of Interest Selection Method for Profiled Side Channel Attacks
Nowadays, one of the most powerful side channel attacks (SCA) is profiled attack. Machine learning algorithms, for example support vector machine,...
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A novel image denoising algorithm and its application in UAV inspection of oil and gas pipelines
For the problem of blurred images in the process of UAV video inspection of oil and gas pipelines, a PSO-2D-VMD-BD denoising algorithm is proposed in...
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Financial Time Series Forecast of Temporal Convolutional Network Based on Feature Extraction by Variational Mode Decomposition
The analysis and forecasting of non-stationary financial data with artificial intelligence techniques are useful for comprehending the future...
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Decomposed intrinsic mode functions and deep learning algorithms for water quality index forecasting
The water quality index (WQI) serves as a global representation of river water quality (WQ). Existing studies related to the WQI have mainly focused...
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A new approach for the detection of abnormal heart sound signals using TQWT, VMD and neural networks
Phonocardiogram (PCG) plays an important role in evaluating many cardiac abnormalities, such as the valvular heart disease, congestive heart failure...
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Variational mode decomposition and bagging extreme learning machine with multi-objective optimization for wind power forecasting
A wind power forecast is an useful support tool for planning and operating wind farm production, facilitating decisions regarding maintenance and...
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Multiclass variance based variational decomposition system for image segmentation
Thresholding-based approaches are widely used for image segmentation due to their low computational cost and complexity and ease of implementation....
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RUL prediction for lithium-ion batteries based on variational mode decomposition and hybrid network model
Lithium-ion batteries are widely used in the field of electric vehicles and energy storage due to their superior performance. However, with increased...
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VMD-DMD coupled data-driven approach for visual saliency in noisy images
Human visual system is endowed with an innate capability of distinguishing the salient regions of an image. It do so even in the presence of noise...
