Fast self-organizing of n-dimensional topology maps

The self-organizing algorithm, proposed in this contribution, is more efficient than the original one, because it starts at a coarse lattice and refines the lattice of the map using spline interpolation at well determined learning steps until a quantization criteria is reached. Therefore the feature map becomes self-growing. The proposed algorithm also includes a hierarchical search for the nearest neighbour. All these enhancements lead to a time complexity of order O(logN) of the self-organizing algorithm for a nA-dimensional map with N neurons in each dimension.