This paper proposes a new method based on Pitch Synchronous Wavelet Transform (PSWT), used for denoising ECG from noisy components. In this paper, we focus on the EMG frequently prcsent in the ECG. This representation is based on a modelling concept, which is able to capture period-toperiod fluctuations of the signal by means of basis elements that are comb-like in the frequency domain. The application of this method on the corrupted signal permits to recover the denoised ECG. The performance of the proposed technique is evaluated on a variety of ECG signals (synthetic and real data) and experimental results show the accuracy of the proposed technique for ail corrupted ECG tested.

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Abstract-In recent years, considerable effort has been devoted to study the biological data sets within the framework of the genomic signal processing field. However, the enormous amount of data deposited into public databases makes the search for useful information a difficult task. Effectively, the choice for a convenient analysis approach is not at all obvious at all. In this work, we provide a new way to map the genomes within the form of images. The mapping uses the Complex Morlet wavelet as analysis technique and the Frequency Chaos Game Signal (FCGS) as digital dataset. Before processing the wavelet analysis, we build the FCGS in such a way that we can follow the frequency evolution of nucleotides' occurrence along the genome. The time-frequency analysis of the FCGS signals constitutes a pertinent tool for exploring the DNA structures in the C.elegans genome-wide landscape.