Results 221 to 230 of about 10,724 (247)
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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.
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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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Journal of Cosmology and Astroparticle Physics, 2022
Abstract Inflationary α-attractor models can be naturally implemented in supergravity with hyperbolic geometry. They have stable predictions for observables, such as ns = 1 - 2/Ne , assuming that the potential in terms of the original geometric variables, as well as its derivatives, are not ...
Kallosh, Renata, Linde, Andrei
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Abstract Inflationary α-attractor models can be naturally implemented in supergravity with hyperbolic geometry. They have stable predictions for observables, such as ns = 1 - 2/Ne , assuming that the potential in terms of the original geometric variables, as well as its derivatives, are not ...
Kallosh, Renata, Linde, Andrei
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Random Point Attractors Versus Random Set Attractors
Journal of the London Mathematical Society, 2001Summary: The notion of an attractor for a random dynamical system with respect to a general collection of deterministic sets is introduced. This comprises, in particular, global point attractors and global set attractors. After deriving a necessary and sufficient condition for existence of the corresponding attractors it is proved that a global set ...
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Modern Physics Letters B, 2006
In this paper, Chen's attractor is scaled via the one-way coupling approach and the adaptive control approach. The proposed method is theoretically analyzed and numerically studied. And the numerical simulations are in line with the theoretical analysis.
Li, Changpin, Deng, Weihua
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In this paper, Chen's attractor is scaled via the one-way coupling approach and the adaptive control approach. The proposed method is theoretically analyzed and numerically studied. And the numerical simulations are in line with the theoretical analysis.
Li, Changpin, Deng, Weihua
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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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