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May 21, 2026Open Access

Frozen Multistable Attractors in Hebbian Adaptive Vector Networks

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Authors

EMEdher Alan Arteaga Marroquin

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Overview

Numerical experiments characterize the dynamics of Hebbian adaptive networks, revealing key properties and implications.

Key Points

  • This research aims to understand the long-term behavior of Hebbian adaptive vector networks and their emergent properties.
  • Conducted systematic numerical experiments on various initial graph topologies
  • Assessed properties such as structural freezing and local basin stability
  • Evaluated the system's response to perturbations and identified hysteresis effects.
  • Identified that edge weights converge to absorbing states, indicating structural freezing.
  • Demonstrated that different initial conditions lead to distinct frozen configurations, showcasing multiplicity of attractors.
  • Found that small perturbations converge to nearby attractors, confirming local basin stability.

Cite This Study

Edher Alan Arteaga Marroquin (2026) studied this question.

synapsesocial.com/papers/6a0ea1c1be05d6e3efb60830https://doi.org/10.5281/zenodo.20281312
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