Fourier neural networks
Adrian Silvescu · 2003
A new kind of neuron model that has a Fourier-like in/out function is introduced. The model is discussed in a general theoretical framework and some completeness theorems are presented. Current experimental results show that the new model outperforms, by a large margin both in representational power and convergence speed, the classical mathematical model of neuron based on weighted sum of inputs filtered by a nonlinear function. The new model is also appealing from a neurophysiological point of view because it produces a more realistic representation by considering the inputs as oscillations.