Abstract
We study a deterministic parallel feed-forward neural network. Exact results for the response of the network are presented; given an initial state that has finite overlap with one stored random key pattern, we calculate the overlap on all subsequent layers (time steps). A region of good recall is separated by a first-order line from one of vanishing asymptotic overlap. Relaxation time to the limiting state is shown to diverge at the overloading transition.
Full Text 
Sign-in/Register to access full text options
Sign-in/Register to access full text options 
Published version (
Free)
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
