{'fraction_non_alphanumeric': 0.011152416356877323, 'fraction_numerical': 0.0, 'mean_word_length': 6.092105263157895, '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}}
Uniform Quantized Synchronization for Chaotic Neural Networks with Successive Packet Dropouts

In this paper, the problem of uniform quantized synchronization is investigated for chaotic neural networks with packet dropouts. By means of the stochastic analysis approach and inequality technique, sufficient conditions are derived under which the synchronization error system is exponentially ultimately bounded in mean square. Finally, a numerical example is provided to validate the feasibility and effectiveness of the proposed results.