{'fraction_non_alphanumeric': 0.01411764705882353, 'fraction_numerical': 0.0, 'mean_word_length': 5.303703703703704, '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}}
Analysis of the Time Constant for the Sigmoidal Algorithm Applied to Biomedical Signals

The time constant along with misadjustment offer a manner of analyzing the convergence behavior of adaptive algorithms, which are largely used to process biomedical signals, mainly regular ones such as cardiac signals. However, some equations found for the time constant suggested in the literature are noise dependent, yielding infinite value for the noiseless case, which is obviously wrong. This problem may explain the fact that no actual comparison of the found equations to practically derived time constant were shown in the literature. In this work we analyze the time constant for updating the weights for the sigmoidal algorithm (SA) when it is used to carry out adaptive estimation of the cardiac component of the impedance cardiographic (ICG) signal