{'fraction_non_alphanumeric': 0.015367727771679473, 'fraction_numerical': 0.0021953896816684962, 'mean_word_length': 5.2465753424657535, '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}}
Prony-Householder method applied to 31P NMR signals: I. Description of the method and application to simulated signals

The Prony method in connection with Burg, Householder and singular value decomposition algorithms for the computation of the autoregressive coefficients, has been applied to simulated signals with different signal to noise ratios. The lines in the frequency domain are characterized by large linewidths and small differences in chemical shifts. The analysis performed by comparing FFT and the above mentioned methods shows that the best results, as far as both stability and performances of the solutions are concerned, are reached by the Prony-Householder method. Furthermore, the authors describe and apply the criterion of the minimum of the residual norm as a new procedure to find the order of autoregression. A validation procedure based on analysis of the residuals is also described.