Storage capacity of memory networks with binary couplings

Storage capacity of memory networks with binary couplings

2014 We study the number p of unbiased random patterns which can be stored in a neural network of N neurons used as an associative memory, in the case where the synaptic efficacies are constrained to take the values ± 1. We find a solution with one step of replica symmetry breaking à la Parisi. This solution gives a critical capacity 03B1c = p/N~ 0.83 which seems to agree with known numerical r...

Diluted neural networks with binary couplings: a replica symmetry breaking calculation of the storage capacity

Autoassociative Memory with high Storage Capacity

The general neural unit (GNU) 1] is known for its high storage capacity as an autoassociative memory. The exponential increase in its storage capacity with the number of inputs per neuron is far greater than the linear growth in the famous Hoppeld network 2]. This paper shows that the GNU attains an even higher capacity with the use of pyramids of neurons instead of single neurons as its nodes....

Embedded Patterns, Indirect Couplings with Randomness, and Memory Capacity in Neural Networks

In the present paper, the neural networks theory based on presumptions of the Ising model is considered. Indirect couplings, the Dirac distributions and the corrected Hebb rule are introduced and analyzed. The embedded patterns memorized in a neural network and the indirect couplings are considered as random. Apart from the complex theory based on Dirac distributions the simplified stationary m...

Storage capacity of the reversed wedge perceptron with binary connections