Robust Exponential Memory in Hopfield Networks
نویسندگان
چکیده
منابع مشابه
Robust Exponential Memory in Hopfield Networks
The Hopfield recurrent neural network is a classical auto-associative model of memory, in which collections of symmetrically coupled McCulloch-Pitts binary neurons interact to perform emergent computation. Although previous researchers have explored the potential of this network to solve combinatorial optimization problems or store reoccurring activity patterns as attractors of its deterministi...
متن کاملSupplemental Information : “ Robust exponential memory in Hopfield networks ”
For an integer r ≥ 0, we say that state x∗ is r-stable if it is an attractor for all states with Hamming distance at most r from x∗. Thus, if a state x∗ is r-stably stored, the network is guaranteed to converge to x∗ when exposed to any corrupted version not more than r bit flips away. For positive integers k and r, is there a Hopfield network on n = ( 2k 2 ) nodes storing all k-cliques r-stabl...
متن کاملSupplemental Information : “ Robust exponential memory in 1 Hopfield networks ”
6 In this supplementary material, we elaborate on the mathematics involved in the 7 claims of the main paper.
متن کاملRobust exponential binary pattern storage in Little-Hopfield networks
The Little-Hopfield network is an auto-associative computational model of neural memory storage and retrieval. This model is known to robustly store collections of randomly generated binary patterns as stable-points of the network dynamics. However, the number of binary memories so storable scales linearly in the number of neurons, and it has been a longstanding open problem whether robust expo...
متن کاملRobust exponential Little-Hopfield network storage
The Little-Hopfield network is an auto-associative computational model of neural memory storage and retrieval. This model is known to robustly store collections of randomly generated binary patterns as stable-states of the network dynamics. However, the number of binary memories so storable scales linearly in the number of neurons, and it has been a long-standing open problem whether robust exp...
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ژورنال
عنوان ژورنال: The Journal of Mathematical Neuroscience
سال: 2018
ISSN: 2190-8567
DOI: 10.1186/s13408-017-0056-2