AI RESEARCH
Randomized Atomic Feature Models for Physics-Informed Identification of Dynamic Systems
arXiv CS.LG
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ArXi:2605.14351v1 Announce Type: cross We present a physics-informed framework for system identification based on randomized stable atomic features. Impulse responses are represented as random superpositions of stable atoms, namely damped complex exponentials associated with poles sampled inside a prescribed disk. Identification is then cast as a convex regularized least-squares problem with optional linear, second-order-cone, and KYP constraints.