? 2024 Elsevier B.V.Variational Mode Decomposition(VMD) method was proposed to separate non-stationary signal mixture by solving a optimization problem. This method is powerful and can reconstruct the signal co
Nonlinear Chirp Mode Decomposition: A Variational Method, IEEE Transactions on Signal Processing, 2017. and the paper: Chen S, Dong X, Xing G, et al, Separation of Overlapped Non-Stationary Signals by Ridge Path Regrouping and Intrinsic Chirp Component Decomposition, IEEE Sensors Journal, 2017. ...
Variational mode decomposition WP: Wind power WS: Wind speed WSTI-RNN: Wind Speed and Turbulence Intensity-based Recursive Neural Network WS: Wind speed References Ishugah TF, Li Y, Wang RZ, Kiplagat JK (2014) Advances in wind energy resource exploitation in urban environment: a review...
characteristic scale decomposition [24], Hilbert vibration decomposition [25], empirical wavelet transform (EWT) [26], null space pursuit [27], nonlinear mode decomposition [28], adaptive local iterative filtering [29], nonlinear sparse mode decomposition [30], and variational mode decomposition (...
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Several effective techniques have been established to find the clear and specific solutions of nonlinear models for instance such as machine learning methods36, He’s variational direct technique37, the discrete mean-field stochastic systems38, bistable origami flexible gripper39, the breather wave ...
The singular value decomposition and spectral norm of a matrix are ubiquitous in numerical analysis. They are extensively used in proofs, but usually it is... SM Rump - 《Bit Numerical Mathematics》 被引量: 45发表: 2011年 Verified bounds for singular values, in particular for the spectral nor...
Moreover, as we show below, when hi( ⋅ ) includes nonpairwise interactions, multilayer interactions, or time-varying interactions, it leads to additional coupling matrices C(k) in the variational equation. Consequently, the variational equations for complex synchronization patterns on ...
In recent research, many vibration-based methods, such as deconvolution [3], variational mode decomposition [4], morphological undecimated wavelet [5], empirical mode decomposition [6], have been proposed for rolling bearing fault detection under a stable working condition. However, the bearing signa...
recognition. They either learn a suitable visual-semantic embedding space [5], [6] or transform this problem to a traditional supervised problem by generating the synthetic instances for unseen classes using the variational autoencoder (VAE) or the generative adversarial networks (GAN) [7], [8]...