{'fraction_non_alphanumeric': 0.011904761904761904, 'fraction_numerical': 0.0, 'mean_word_length': 5.468531468531468, '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}}
Improved Dual Tone Multi Frequency identification Using Adaptive Resampling Particle Filter

This paper is concerned with the improvement of the Dual Tone Multi Frequency (DTMF) identification where the signals were transmitted via real communication channels. The frequencies of the DTMF signals are tracked using particle filtering method, a method that rely on the numerical computation in approximating the posterior probability density function (PDF) of the underlying state parameters, to identify which pad was pressed at the transmitter end. We propose and implement the adaptive resampling to improve the performance of the DTMF identification. The method enhances the quality of resampling stage generating a better set of particles which will be used for posterior PDF of the tones of the DTMF signals. Results reveal the advantage of using the proposed method in comparison to the conventional resampling scheme.