As. Galanopoulos et Sc. Ahalt, CODEWORD DISTRIBUTION FOR FREQUENCY SENSITIVE COMPETITIVE LEARNING WITH ONE-DIMENSIONAL INPUT DATA, IEEE transactions on neural networks, 7(3), 1996, pp. 752-756
We study the codeword distribution for a conscience-type competitive l
earning algorithm, frequency sensitive competitive learning (FSCL), us
ing one-dimensional input data, We prove that the asymptotic codeword
density in the limit of large number of codewords Is given by a power
law of the form Q(x) = C . P(x)(alpha), where P(x) is the input data d
ensity and alpha depends on the algorithm and the form of the distorti
on measure to be minimized, We further show that the algorithm can be
adjusted to minimize any L(p) distortion measure with p ranging in (0,
2].