arXiv (All)
open access
Prediction Error Method for Identification of Subnetworks of Dynamical Systems
This paper considers prediction-error identification of a subnetwork embedded in a dynamic network. Measured boundary signals entering the subnetwork are appended to the exogenous inputs. Consistency requires that the part of these boundary signals generated by the subnetwork be reconstructible from
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Adaptive machine learning models for predictive maintenance in industrial internet of things (IIoT) systems.#25726
- FaultFormer: Pretraining Transformers for Adaptable Bearing Fault Classification#1233653
- Urban Power Grid Topology and Hierarchy Identification from Open Data#1297179
- Source Identification Approaches for EMC and SI Issues : Opening Towards Machine Learning Models#1235236
- Inference of Unknown Dynamical Components Using Next Generation Reservoir Computing: From Chaotic Systems to Climate Data#1028695
Record · ID 1215653
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive