Saeed Eftekhar Azam
Artificial Intelligence · 2012–2015
A researcher in the Science corpus: 2 papers; trusts 13 researchers and is trusted by 2 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 12 citations into it; #29,126 of 35,345 by trust here, #34,943 by citations
- Civil and Structural Engineering — 12 citations into it; #4,652 of 6,160 by trust here, #6,082 by citations
- Control and Systems Engineering — 11 citations into it; #6,700 of 8,257 by trust here, #8,083 by citations
- Statistics and Probability — 5 citations into it
Whom Saeed Eftekhar Azam trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Steven Gillijns
- Eric M. Hernandez
- Edwin Reynders
- Costas Papadimitriou
- E. Lourens
- Stefano Mariani
- Dionisio Bernal
- Guido De Roeck
- Jianye Ching
- B. De Moor
Who trusts Saeed Eftekhar Azam overall
Papers from Saeed Eftekhar Azam's perspective
Ordered by how strongly the researchers Saeed Eftekhar Azam trusts endorse each paper. Same corpus, a different order for every researcher.
- Joint input-response estimation for structural systems based on reduced-order models and vibration data from a limited number of sensors
- A natural observer for optimal state estimation in second order linear structural systems
- Reference-based combined deterministic–stochastic subspace identification for experimental and operational modal analysis
- The effect of prediction error correlation on optimal sensor placement in structural dynamics
- Bayesian State and Parameter Estimation of Uncertain Dynamical Systems
- Unbiased minimum-variance input and state estimation for linear discrete-time systems with direct feedthrough (at - Automatisierungstechnik)
- General Realization Algorithm for Modal Identification of Linear Dynamic Systems
- Robust two-stage Kalman filters for systems with unknown inputs (IEEE Transactions on Automatic Control)
- Fatigue predictions in entire body of metallic structures from a limited number of vibration sensors using Kalman filtering
- Sequential deconvolution input reconstruction