Luttrell S P, 1990, Derivation of a class of training algorithms, IEEE Transactions on Neural Networks, vol. 1, no.2, pp. 229-232
This paper presents a novel derivation of Kohonen's topographic mapping training algorithm, based upon an extension of the Linde-Buzo-Gray (LBG) algorithm for vector quantiser design. Thus a vector quantiser is designed by minimising an L2 reconstruction distortion measure, including an additional contribution from the effect of code noise which corrupts the output of the vector quantiser. The neighbourhood updating scheme of Kohonen's topographic mapping training algorithm emerges as a special case of this code noise model. This formulation of Kohonen's algorithm is a specific instance of the 'robust hidden layer principle', which stabilises the internal representations chosen by a network against anticipated noise or distortion processes.