Geometric interpretation

• Both weights & input patterns can be seen as vectors in a hyper space

• Euclidian normalisation [? (wij)2 = 1]

  • all vectors on a sphere in space of n dimensions (n = number of inputs)
  • node with weight vector closest to input vector is winner

• Linear normalisation [? wij = 1]

  • all weights on a plane