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• To account for the variation of EDF’s (the French electrical company) portfolio following the liberalization of the electrical market, it is essential to disaggregate the global load curve. The idea is to disaggregate the global signal in such a way that the sum of disaggregated forecasts significantly improves the prediction of the whole global signal.(More)
Wavelet transform is a powerful tool to analyze the non-stationary biomedical signals. This paper deals with the noise removal of ECG signal using three different wavelet families (haar, Daubechies and Symlets). The different noise structure (unscaled white noise, scaled white noise and non white noise) have been selected for ECG signals and compared their(More)
Several noise removal techniques have proven their worth in image processing applications. After an overview of some image denoising approaches, we introduce a LMMSE-based denoising technique with wavelet multiscale model and wiener filter in spatial domain. This proposed denoising technique stands out prominent in terms of SNR, MSE and PSNR compared to(More)
Electroencephalogram (EEG) signals are of having very small amplitudes and so these can be easily contaminated by different Artifacts. Due to the presence of various artifacts in EEG, its analysis becomes difficult for the clinical evaluation. Major types of artifacts that affect the EEG are Power Line noise, eye movements, Electromyogram (EMG), and(More)
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