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For instance, an HNeT assembly comprised of 1000 cortical memory elements and processing, on average, 2nd order combinatorics would require the processing resource shown to the left. Computational overhead is linearly proportional to that required within a single neuron cell within traditional multi-cell, multi-layered ANS systems such as back-propagation (by a factor of 4). Both rate of learning convergence and associative storage capacity for the neuro-holographic method dramatically exceeds that of conventional neural network architectures.
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