{'fraction_non_alphanumeric': 0.006837606837606838, 'fraction_numerical': 0.0, 'mean_word_length': 5.43956043956044, '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}}
A fuzzy adaptive filter for system identification

An adaptive fuzzy filter and its use for system identification is proposed. This filter proposes a fuzzy adaptation algorithm which uses the reference signal and the error signal as inputs and the multiplication of the reference signal by the approximated weight as an output, which avoids the use of multiplication circuits for its implementation in VLSI. Simulation results show that the proposed adaptive fuzzy filter outperforms the conventional LMS adaptive filter used for system identification with its faster convergence rate.