Figure 6.

A self-organizing feature map trained by Kohonen's winner-take-all algorithm. Graphs depict frequency contours over short time-frames (approx. 100 ms) for Finnish phonemes. (a) Points along the contour served as inputs to a map. (b) In a trained map, adjacent neurons map similar space. The phoneme in (a) is most similar to the ‘winning’ neuron at the centre of the concentric grey circles. In a training phase, the winning neuron would cause the neighbouring neurons to update their weights to be more similar to the winning weights. This neighbourhood function drives the map's ability to topographically map complex stimuli. Figure modified from Kohonen (2003).