Inferring bifurcation diagrams of two distinct chaotic systems by a single machine
We propose a dual-channel reservoir-computing scheme for inferring the dynamics of two distinct chaotic systems with a single machine. By augmenting a standard reservoir with a system-label channel and a parameter-control channel, the machine can be trained from time series collected from a few sampled states of the two systems. We show that the trained machine not only predicts the short-time evolution of the sampled states, but also reproduces the long-term statistical properties of unseen states, thereby enabling reconstruction of the bifurcation diagrams of both systems from partial observations. The effectiveness of the scheme is demonstrated for the Lorenz and Rössler systems in num...
| Authors | Jianmin Guo, Yao Du, Yizhen Yu et al. |
|---|---|
| Primary category | nlin.CD |
| Published | 29 April 2026 |
| Last updated at source | 29 April 2026 |
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