Basin Geometry and Reliable Recall of Dynamical Memories in Reservoir Computing
Reliable attractor recall conventionally requires broad basins of attraction. However, in reservoir-computing based associative memory, temporal cues reliably recover dynamical memories despite basins dominated by unpredictable, riddled-like regions. We reveal that memory basins exhibit an ``octopus-like'' structure: a robust ``head'' near the attractor and thin, intertwined ``tentacles'' spanning state space. Initial states in tentacular regions yield near-zero uncertainty exponents, making the recalled memory effectively unpredictable at finite precision. Yet, cue-driven generalized synchronization bypasses this unpredictability, driving the system into the robust basin head. This mecha...
| Authors | Ling-Wei Kong, Ying-Cheng Lai |
|---|---|
| Primary category | nlin.CD |
| Published | 1 September 2026 |
| Last updated at source | 1 September 2026 |
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