  This paper presents a Fast Synchronization Clustering algorithm (FSynC),
which is an improved version of SynC algorithm. In order to decrease the time
complexity of the original SynC algorithm, we combine grid cell partitioning
method and Red-Black tree to construct the near neighbor point set of every
point. By simulated experiments of some artificial data sets and several real
data sets, we observe that FSynC algorithm can often get less time than SynC
algorithm for many kinds of data sets. At last, it gives some research
expectations to popularize this algorithm.
