منابع مشابه
Storage capacity of two-dimensional neural networks.
We investigate the maximum number of embedded patterns in the two-dimensional Hopfield model. The grand state energies of two specific network states, namely, the energies of the pure-ferromagnetic state and the state of specific one stored pattern are calculated exactly in terms of the correlation function of the ferromagnetic Ising model. We also investigate the energy landscape around them a...
متن کاملStorage capacity and dynamics of nonmonotonic networks
This work investigates the retrieval capacities of di erent types of nonmonotonic neurons. Storage capacity is maximized when the neuron response is a function with well de ned geometrical characteristics. Numerical experiments demonstrate that storage capacity is directly related to the dynamical property of the iterative map that describes the network evolution. Maximum capacity is reached wh...
متن کاملAn Influence of Nonlinearities to Storage Capacity of Neural Networks
The more realistic neural soma and synaptic nonlinear relations and an alternative mean field theory (MFT) approach relevant for strongly interconnected systems as a cortical matter are considered. The general procedure of averaging the quenched random states in the fully-connected networks for MFT, as usually, is based on the Boltzmann Machine learning. But this approach requires an unrealisti...
متن کاملOptimal storage capacity of neural networks at finite temperatures
Gardner's analysis of the optimal storage capacity of neural networks is extended to study finite-temperature effects. The typical volume of the space of interactions is calculated for strongly-diluted networks as a function of the storage ratio α, temperature T , and the tolerance parameter m, from which the optimal storage capacity α c is obtained as a function of T and m. At zero temperature...
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ژورنال
عنوان ژورنال: IEEE Transactions on Information Theory
سال: 2015
ISSN: 0018-9448,1557-9654
DOI: 10.1109/tit.2015.2472521