{'fraction_non_alphanumeric': 0.015410958904109588, 'fraction_numerical': 0.008561643835616438, 'mean_word_length': 5.428571428571429, '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}}
Periodicity Detection in Nonautonomous Dierence Equations

System identification for nonlinear differential and difference equations has lagged far behind the linear case, due to the greater complexity of the task. Takens’ Theorem [1,10] of 25 years ago opened a new avenue of investigation, introducing geometric methods that were essential for nonlinear problems. The ramifications of this result have unfolded in an area that has become known as attractor reconstruction. A particular case we will consider in this article is a system of driven difference equations of general form