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The proposed approach is compared to the correlation based wavelet selection (CBWS) and to the energy based wavelet selection (EBWS) methods for signals simulated and obtained from high voltage equipment, showing better filtering performance for over 70% of the tested signals and a smaller processing time.
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Therefore, electrical signals will require a broader set of tools and methods for signal processing.
The time series provide the input for statistical methods for signal generation, CUSUM and Farrington.
Spectral analysis[1] and wavelet analysis[2 4] are popular methods for signal decomposition.
Nonlinear diffusion filtering and wavelet/frame shrinkage are two popular methods for signal and image denoising.
Typical methods for signal analysis utilize the Fourier Transform-based algorithms to estimate the spectral response of a signal.
Off-line data analysis includes more advanced techniques like beam forming and time delay methods for signal direction reconstruction.
Much research is needed on developing methods for signal processing and analysis of CFRP-laminate impact data points.
The main aim of this study is to define an approach for the emotion recognition from speech taking into account biologically inspired methods for signal representation and classification.
The results of the implemented evaluation functionalities show the feasibility of the implemented methods for signal processing, in view of enhanced smart grid operation.
We provide guidelines for determination of the localization of SNAREs by immunofluorescence microscopy including methods for signal amplification, antigen retrieval, and suppression of antibody cross-reactivity.
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