{'fraction_non_alphanumeric': 0.023728813559322035, 'fraction_numerical': 0.003389830508474576, 'mean_word_length': 5.640449438202247, 'pattern_counts': {'":': 0, '<': 1, '<?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}}
Harmonic Retrieval from Coarsely Quantized Measurements

We consider the problem of harmonic retrieval from coarsely quantized measurements. We formulate the sinusoidal parameter estimation problem into a sparse parameter estimation problem by adding an lq-norm (0 < q ≤ 1) based penalty term to the negative log-likelihood function. A user parameter-free algorithm is devised to solve the problem efficiently by using the cyclic optimization and majorization-minimization (MM) techniques. Numerical examples are provided to demonstrate the estimation performance of the proposed algorithm.