Density-based clustering with topographic maps
Marc M. Van Hulle · IEEE Transactions on Neural Networks · 1999
A new unsupervised competitive learning rule is introduced, called the kernel-based Maximum Entropy learning Rule (kMER), for equiprobabilistic topographic map formation. The application envisaged is density-based clustering. An empirical study is conducted to compare the clustering performance of kMER with that of a number of other unsupervised competitive learning rules.