Kolmogorov learning for feedforward networks
Roman Neruda, A. Stedry, Jitka Drkošová · 2002
We present a learning algorithm for feedforward neural networks that is based on Kolmogorov theorem concerning composition of a n-dimensional continuous function from a one-dimensional continuous functions. A thorough analysis of the algorithm time complexity is presented for its serial and parallel implementation.