  In this paper, I will introduce a fast and novel clustering algorithm based
on Gaussian distribution and it can guarantee the separation of each cluster
centroid as a given parameter, $d_s$. The worst run time complexity of this
algorithm is approximately $\sim$O$(T\times N \times \log(N))$ where $T$ is the
iteration steps and $N$ is the number of features.
