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Figure 1 | BMC Neuroscience

Figure 1

From: Efficient supervised learning in networks with binary synapses

Figure 1

Learning capacity and learning time. (left) achieved capacity vs. the number of synapses N, with different numbers of hidden states, in the sparse coding case: the algorithm can achieve up to 70% of the maximal theoretical capacity at N ~10000 with 10 hidden states; (right) average learning time (number of presentations per pattern) versus number of patterns to be learned, for N = 64000: less than 100 presentations are required up to the critical point where learning fails.

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