{'fraction_non_alphanumeric': 0.01651376146788991, 'fraction_numerical': 0.0, 'mean_word_length': 5.198863636363637, '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}}
Noise cancellation in musical signals using adaptive filtering algorithms

Applications of Digital Signal Processing inflict substantial constraints on area, speed, power dissipation and cost. ASIC, DSP and FPGA are the different tools to meet the constraints. In most of the situations where signals are highly fluctuating i.e. signals are varying with time, fixed filters which are designed with the fixed parameters cannot be used therefore one can go for adaptive filters. For the cancellation of noise signal adaptive filtering technique is used. In many applications of noise cancellation the changes in signal is quite fast. This requires adaptive algorithm, which converge rapidly. From this point of view LMS and Averaging algorithms suit these situations best. LMS algorithm is one of the most used algorithms in many signal processing applications. Unfortunately LMS algorithm has high computation complexity and stability problems. In order to overcome these problems averaging algorithm can be used, where high convergence rate cab be achieved compare to that of LMS algorithm.