{'fraction_non_alphanumeric': 0.020676691729323307, 'fraction_numerical': 0.0, 'mean_word_length': 4.793478260869565, '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}}
Decreasing Noise in Magnetic Anomaly Detection Basing on Wavelet Denoising

Abstract. In the field of magnetic anomaly detection(MAD) under ocean, oceanic waves produce magnetic noise which cannot be ignored. An AR model is used to describe the noise at first. Then the MAD model is built basing on the magnetic dipole model. Finally, a method for decreasing the noise in MAD basing on wavelet denoising is proposed. According to simulation, the way of wavelet denosing has obvious effect on decreasing the noise and increasing SNR.