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Attractor and integrator networks in the brain
Nature Reviews Neuroscience, 2021In this Review, we describe the singular success of attractor neural network models in describing how the brain maintains persistent activity states for working memory, corrects errors and integrates noisy cues. We consider the mechanisms by which simple
Mikail Khona, I. Fiete
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Electronics Letters, 2020
This Letter reports a new no-equilibrium chaotic system with hidden attractors and coexisting attractors. Bifurcation diagram shows that the proposed system generates chaos through period-doubling bifurcation with the variation of system parameters, and ...
Q. Lai +2 more
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This Letter reports a new no-equilibrium chaotic system with hidden attractors and coexisting attractors. Bifurcation diagram shows that the proposed system generates chaos through period-doubling bifurcation with the variation of system parameters, and ...
Q. Lai +2 more
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Attractors and quasi-attractors of a flow
Journal of Applied Mathematics and Computing, 2007zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Zuo, Chunyan, Wang, Xiaoxia
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Fractals, 1995
When a chaotic signal is used to force a switching-type variable which dependent on the momentary magnitude of the chaotic stimulus either shows a damped or an autocatalytic response, a new dynamical phenomenon arises. It is reminiscent of the “flares” observed in astrophysical situations.
Rossler, Otto E., Hartmann, Georg C.
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When a chaotic signal is used to force a switching-type variable which dependent on the momentary magnitude of the chaotic stimulus either shows a damped or an autocatalytic response, a new dynamical phenomenon arises. It is reminiscent of the “flares” observed in astrophysical situations.
Rossler, Otto E., Hartmann, Georg C.
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WIREs Cognitive Science, 2009
AbstractAn attractor network is a network of neurons with excitatory interconnections that can settle into a stable pattern of firing. This article shows how attractor networks in the cerebral cortex are important for long‐term memory, short‐term memory, attention, and decision making.
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AbstractAn attractor network is a network of neurons with excitatory interconnections that can settle into a stable pattern of firing. This article shows how attractor networks in the cerebral cortex are important for long‐term memory, short‐term memory, attention, and decision making.
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Some properties of attractors and quasi-attractors
Chaos, Solitons & Fractals, 2007zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Neural Computation, 2001
Attractor networks, which map an input space to a discrete output space, are useful for pattern completion—cleaning up noisy or missing input features. However, designing a net to have a given set of attractors is notoriously tricky; training procedures are CPU intensive and often produce spurious attractors and ill-conditioned attractor basins.
Zemel, Richard S., Mozer, Michael C.
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Attractor networks, which map an input space to a discrete output space, are useful for pattern completion—cleaning up noisy or missing input features. However, designing a net to have a given set of attractors is notoriously tricky; training procedures are CPU intensive and often produce spurious attractors and ill-conditioned attractor basins.
Zemel, Richard S., Mozer, Michael C.
openaire +2 more sources