{'fraction_non_alphanumeric': 0.014647137150466045, 'fraction_numerical': 0.0, 'mean_word_length': 5.962962962962963, '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}}
Embedded Adaptive Neuro Fuzzy Inference System with Hardware Implemented Real Time Parameter Update

Abstract In the paper a Sugeno architecture based hardware implemented neuro adaptive inference system’s training algorithm is presented. The block diagram of the neuro-adaptive inference system output computing implemented in hardware is discussed, and the implementation in reconfigurable circuit of real-time parameter tuning is presented. The proposed system functionality based on measurements achieved is demonstrated. The resulted architecture has a very high processing speed, and the parameter adaptation works in parallel with the output processing. The proposed architecture can also be used for different training algorithms’ development.