{'fraction_non_alphanumeric': 0.020512820512820513, 'fraction_numerical': 0.0, 'mean_word_length': 5.401639344262295, '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}}
An Extended Dual Parameterization Method to Constrained Least Square Laguerre Filter Design

The design of peak-constrained weighted least-square error (PCWLSE) Laguerre filters is of interest in signal processing applications. The formulation of such Laguerre filters ends up as a semi-infinite problem with two uncountable variables. Here, an efficient method is proposed to deal with this. Therefore, one can design PCWLSE Laguerre filters to satisfy all the continuous constraints of the problem. Furthermore, the desired phase response is also guaranteed. The proposed method has been developed based on exploiting the dual parameterization scheme derived directly from the Karush-Kuhn-Tucker condition. This approach may also be used to design similar asymmetric FIR filters