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Prog. Theor. Phys. Vol. 104 No. 4 (2000) pp. 709-721
Stability Gap between Off- and On-Firing States in a Coupled Ginzburg-Landau Oscillator Neural Network
Satoshi Kawaguchi
Laboratory for Advanced Brain Signal Processing
Brain Science Institute, RIKEN, Wako 351-0198, Japan
(Received February 17, 2000)
Abstract:
An oscillator neural network based on the Ginzburg-Landau equation
is proposed in order to investigate associative memory. The embedded
patterns include both off- and on-firing states with phase. Neurons
encode not only the phase but also the state of the cell. The system
has a Lyapunov function with wells corresponding to off- and on-firing
states. These two states are characterized by mutual stabilities which
are generally different. Each neuron falls into one of the wells, as
determined by its dynamics.
The storage capacity and the order parameter overlap are studied using
numerical simulations and an ordinary self-consistent signal-to-noise
analysis.
We show that these properties depend crucially on both the potential
parameter and the mean activity levels of the patterns. In the case
of the sparse coding limit, the storage capacity diverges as in the
case of the binary model.
URL :
http://ptp.ipap.jp/link?PTP/104/709/
DOI : 10.1143/PTP.104.709
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Citing Article(s) :
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Progress of Theoretical Physics Vol. 107 No. 5 (2002) pp. 839-860
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Oscillation of the Overlap Parameter in a Phase Coupled Model
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Satoshi Kawaguchi