{'fraction_non_alphanumeric': 0.0182648401826484, 'fraction_numerical': 0.0, 'mean_word_length': 5.544776119402985, '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}}
A General Algorithm Framework Design for Ship-Radiated Noise Target Recognition

Ship-radiated noises are able to reflect feature of same type vessel. This paper designed a general algorithm framework for ship-radiated noise target recognition, and given the design and implementation of key modules. The algorithm framework can improve the identification accuracy, support multi-dimensional feature space , multi-classify unit and heterogeneous classifier, overcome shortcoming of identify target property of single feature and single classifier from only one aspect, so it has widely applicability. The sample assessment mechanism is introduced by the framework, which can eliminate low quality sample in order to improve the identification accuracy and efficiency of training. A simulation example is given and the results shows that the method is reasonable and effective.