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Multitasking Network with Fast Noise by Agliari, Elena; Barra, Adriano; Galluzzi, Andrea; Isopi, Marco is a scholarly article available to read on EtoBox.

What is Multitasking Network with Fast Noise about?

We consider the multitasking associative network in the low-storage limit and we study its phase diagram with respect to the noise level $T$ and the degree $d$ of dilution in pattern entries. We find that the system is characterized by a rich variety of stable states, among which pure states, parallel retrieval states, hierarchically organized states and symmetric mixtures (remarkably, both even and odd), whose complexity increases as the number of patterns $P$ grows. The analysis is performed both analytically and numerically: Exploiting techniques based on partial differential equations, allows us to get the self-consistencies for the order parameters. Such self-consistence equations are then solved and the solutions are further checked through stability theory to catalog their organizations into the phase diagram, which is completely outlined at the end. This is a further step toward the understanding of spontaneous parallel processing in associative networks.

Author

Agliari, Elena; Barra, Adriano; Galluzzi, Andrea; Isopi, Marco

Published

2013

Language

EN