Externally Growing Cell Structures for Pattern Classification

Based on B. Fritzke’s GCS (Growing Cell Structures) we present here a new incremental self-organizing neural network, the Externally Growing Cell Structures (EGCS). Our goals are to speed up the convergence and to improve the generalization performance. The mechanism of internally growing cells in EGCS is the same as in GCS. However, when the Maximum Resource Vertex (MRV) or the Maximum Error Vertex (MEV) is a boundary node, the new cell is grown externally. Simulation results on some neural network benchmarks (two-spiral problem, sonar mine/rock separation problem, Wisconsin breast cancer study) indicate that EGCS performs better than the original GCS, measured by classification rate, the required number of cells and epochs.