Robust exponential Little-Hopfield network storage
نویسندگان
چکیده
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 exponential storage of binary patterns was possible in such a network memory model. In this note, we design simple families of Little-Hopfield networks that provably solve this problem affirmatively. As a byproduct, we produce a set of novel (nonlinear) binary codes with an efficient, highly parallelizable denoising mechanism.1
منابع مشابه
Robust 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...
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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.
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