{'fraction_non_alphanumeric': 0.006134969325153374, 'fraction_numerical': 0.0, 'mean_word_length': 5.102803738317757, '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}}
New efficient and accurate moment matching based model for crosstalk estimation in coupled RC trees

In this paper we provide a new efficient moment matching based model for the estimation of crosstalk in coupled RC tree networks. This model is formulated based on an exact and efficient linear order recursive algorithm for the moment computation of such networks with both lumped and distributed RC elements. The formulas used in the model are efficiently obtained by using the results of moment computation without any matrix operation and can fit for arbitrary input waveforms. Simulation results show it performs better than all existing formulas.