Hybrid fuzzy-clustering algorithm of unevenly and asynchronously spaced time series in computer engineering

In this paper the hybrid fuzzy-clustering algorithm of unevenly and asynchronously spaced time series (such as biomedical data, digital video streams, data from Internet of Things sensors, the signals, which form a discrete two-dimensional field, etc.) is proposed. This algorithm is characterised by computational simplicity, high approximation properties and can be used for clustering both small and high dimension data set of arbitrary nature.