{'fraction_non_alphanumeric': 0.013232514177693762, 'fraction_numerical': 0.0, 'mean_word_length': 5.883116883116883, '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}}
Stability criteria of discrete-time analog neural networks

In this short paper, some globally asymptotical stability criteria for the equilibrium states of a class of discrete-time dynamic neural networks with continuous states and asymmetrical weight matrices are presented. The resulting stability criteria are represented by either the existence of the positive diagonal solutions of the Lyapunov equations or some inequalities. Finally, some examples are provided for demonstrating the global stability conditions presented.