{'fraction_non_alphanumeric': 0.015495867768595042, 'fraction_numerical': 0.0, 'mean_word_length': 4.981481481481482, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Blind separation of wide-band sources in the frequency domain

Conventional antenna array processing techniques are based on the use of second order statistics but rest on restrictive assumptions. Thus, when a priori information about the propagation or the geometry of the array are hardly available, the model can be generalized to a blind sources separation model. It supposes the statistical independence of the sources and their non-Gaussianity. We focus on the generalization of the sources separation problem to convolutive mixtures of wide-band sources in the frequency domain. As the N-point discrete Fourier transform of signals generally tends to be Gaussian when N tends to infinity according to the central limit theorem, we replace the independence criterion of the sources with the independence of a specific MA filtering of their DFT. The result is then an instantaneous complex mixture in time-domain and the new sources are proved to be non-Gaussian.