{'fraction_non_alphanumeric': 0.017333333333333333, 'fraction_numerical': 0.0, 'mean_word_length': 5.418803418803419, '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}}
Improved Results on Passivity Analysis of Neutral-Type Neural Networks with Mixed Time-Varying Delays

This paper is considered with problem of the passivity analysis for neutral-type neural networks with 
mixed time-varying delays. By constructing an augmented Lyapunov-Krasovskii functionals and using the double 
integral inequality with approach to estimate the derivative of the Lyapunov-Krasovskii functionals, sufficient 
conditions are established to ensure the passivity of the considered neutral-type neural networks, in which some 
useful information on the neuron activation function ignored in the existing literature is taken in to account. Finally, 
a numerical example is given to demonstrate the effectiveness of the proposed method.