An analysis of initial state dependence in generalized LVQ

The author proposed a new formulation of learning vector quantisation (LVQ) called generalized LVQ (GLVQ) based on the minimum classification error criterion. In this paper, the initial state dependence in GLVQ is discussed, and it is clarified that the learning rule should be modified to make it insensitive to the initial values of reference vectors. The robustness of the modified GLVQ for the initial state is demonstrated through simulation experiments and compared with the generalized probabilistic descent approach