Optimal Magnification Factors in Self-Organizing Feature Maps

Introduction Kohonen's self-organizing feature maps (SOFMs) [8] usually exhibit a selective magnification of often stimulated regions of their input space. This amounts to a larger transmission of information about the stimulus ensemble than in maps with a constant resolution. Such a selective magnification is not only observed in biological maps, but is also often regarded as a desirable design objective in technical contexts. For at least three reasons, the magnification properties of SOFMs deserve further investigation: 1. An analysis by Ritter and Schulten [10] demonstrated that the SOFM algorithm does not yield a maximum entropy map (i.e. does not transmit the maximum amount of information). 2. As a related argument we observe that it depends on the error criterion one applies which magnification properties are to be regarded as optimal. For example, a minimal worst case error is achieved by maps with all receptive fields (or Voronoy polygons) being of equal extension, i.