Unsupervised Learning in an Ensemble of Spiking Neural Networks Mediated by ITDP
Fig 8
Illustrative images for controlled feature assignment for SEM ensemble networks.
White regions indicate available pixels (active region) as defined by preprocessing, and the Gaussian means for the normal Gaussian selection scheme are evenly placed inside such regions by random placement procedure (See Methods for details of the actual Gaussian mean placement). The number of stretched Gaussian features used increases linearly with ensemble size (see Methods for details). The diameters of red circles and ovals roughly represent the full width at a tenth of maximum (FWTM) for each principal direction (the length of an oval is shown far shorter than it actual is for the sake of visualization—long ovals are used to ensure they form roughly uniform bars in the region of available pixels). In all cases, exactly 1/4 of pixels from the available (white) region are stochastically selected (without replacement) for each ensemble network according to each distribution function.