Kohonen Self-Organising Map with a 24×24 neuron lattice learning to map 3-dimensional RGB colour inputs. Each iteration: sample a random colour from the selected distribution; find the Best Matching Unit (BMU) by minimum Euclidean distance; update the BMU and its neighbourhood with the Gaussian kernel h = exp(−d²/(2σ²)), scaled by learning rate α. Both α and σ decay exponentially over time. The map self-organises from random noise into a smooth topology-preserving colour gradient.

← Machine Learning

Self-Organising Map 🗺️

UK
Iteration0
α (learn)0.500
σ (radius)8.00
BMU flash

Neurons576
Input dimRGB (3D)
Colour Input
Speed Medium