Unsupervised Learning in an Ensemble of Spiking Neural Networks Mediated by ITDP
Fig 7
Examples of ensemble behaviours (NE = 9) for different gating network performances ((A) better than, (B) similar to, (C) worse than the ensemble average).
All the ensemble and the gating WTAs used random feature selection. The colors represent the NCEs of the final network (red), the gating network (blue), the ensemble networks (grey) and their average (black). Vertical lines indicate the time span of the total data presentation, where input data are sequentially presented for multiple rounds in order to see long term convergence. The NCE value at time t is calculated by counting the class-dependent spikes within the past finite time window of [Tp, t] (Tp < t). In order to prevent a sudden change in the NCE plots due to the exclusion of the early system output (which are immature resulting in high NCE values) from the time window, Tp was dynamically changed for faster burn-out of those initial values as: Tp = t(1−d/4D) where d = t when t < 2D and d = 2D otherwise, D = 224sec is the duration of one round of dataset presentation. See Methods for details of the NCE calculations.