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The focus of this master thesis is to use a new signal processing technique, the Qp transform in a recent machine algorithm LensID to enhance the detection rate of gravitational wave signals lensed by galaxies. First, we will introduce the concept associated with gravitational waves, signal processing and machine learning. Second, we will present one measured signal which is part of a lensing study, GW191105, where the Qp transform helps to distinguish a gravitational wave better. Third, we will show various examples of injected lensed signals which are better recognised with their characteristic chirp evolution. Finally, a discussion of the implementation of this technique with LensID and the associated improvement will be presented. Finally, we summarise our main findings and future prospects.

Gravitational Waves --- General Relativity --- Signal Processing --- Machine Learning --- Q Transform --- Qp Transform --- LensID Algorithm --- Spectrogram Analysis --- Transient Signals --- Noise Reduction --- Lensed Gravitational Waves --- GW191105 --- Neural Networks --- Astrophysics --- Fourier Transform --- Wavelet Transform --- Time-Frequency Analysis --- Data Analysis --- Detection Techniques --- Astronomy --- Cosmic Events --- Physique, chimie, mathématiques & sciences de la terre > Physique --- Physique, chimie, mathématiques & sciences de la terre > Aérospatiale, astronomie & astrophysique