{'fraction_non_alphanumeric': 0.009596928982725527, 'fraction_numerical': 0.0, 'mean_word_length': 4.673913043478261, '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}}
Spike train decoding scheme for a spiking neural network

A spiking neural network models a type of biological neural system in which spike trains are used to convey information, is presented. A spike train consists of a series of asynchronous input spikes which are input into a neuron through a synapse. A new decoding scheme which can uniquely distinguish spike trains by using the relative spike arrival times in a spike train is proposed. Only a limited number of neurons are needed to implement the decoding scheme.