{'fraction_non_alphanumeric': 0.00723589001447178, 'fraction_numerical': 0.0, 'mean_word_length': 5.348623853211009, '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 neural adaptive array antenna to reduces interference signals in communications systems

We consider arrays of elements equally spaced on a linear disposition. Our purpose is to determine the excited elements which optimize the signal interference ratio of an array. The problem of minimizing the signals received from interfering or undesirable signal sources by appropriately modifying the antenna radiation pattern is addressed. A neural network is used to arrive at an optimum set of array excitations to achieve a specified radiation pattern. A linear array antenna with six elements was proposed to evaluate the performance of the neural network controller for reducing interference.