# Structured identification for network reconstruction of RC-models

arXiv: https://arxiv.org/abs/2007.10046 · HTML: https://mlsanity.com/paper/2007.10046/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 20 Jul 2020.

## Built on by (most cited first, 1 of 1)

- [Distributed Sensing Along Fibres for Smart Clothing](https://mlsanity.com/paper/2402.09057/) (2024)

## Abstract (arXiv)

Resistive-capacitive (RC) networks are used to model various processes in engineering, physics or biology. We consider the problem of recovering the network connection structure from measured input-output data. We address this problem as a structured identification one, that is, we assume to have a state-space model of the system (identified with standard techniques, such as subspace methods) and find a coordinate transformation that puts the identified system in a form that reveals the nodes connection structure. We characterize the solution set, that is, the set of all possible RC-networks that can be associated to the input-output data. We present a possible solution algorithm and show some computational experiments.