Physics – Condensed Matter – Disordered Systems and Neural Networks
Scientific paper
1998-12-11
Physics
Condensed Matter
Disordered Systems and Neural Networks
9 pages, 3 Postscript figures, uses epsbox.sty
Scientific paper
10.1103/PhysRevLett.83.1062
Little is known theoretically about the associative memory capabilities of neural networks in which information is encoded not only in the mean firing rate but also in the timing of firings. Particularly, in the case that the fraction of active neurons involved in memorizing patterns becomes small, it is biologically important to consider the timings of firings and to study how such consideration influences storage capacities and quality of recalled patterns. For this purpose, we propose a simple extended model of oscillator neural networks to allow for expression of non-firing state. %which is able to memorize sparsely coded phase patterns including non-firing states. Analyzing both equilibrium states and dynamical properties in recalling processes, we find that the system possesses good associative memory.
Aoyagi Toshio
Nomura Masaki
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