A Framework for Simulating and Estimating the State and Functional Topology of Complex Dynamic Geometric Networks
DOI10.1162/NECO_a_00065zbMath1211.68496arXiv0908.3934WikidataQ51645467 ScholiaQ51645467MaRDI QIDQ3070787
Marius Buibas, Gabriel A. Silva
Publication date: 26 January 2011
Published in: Neural Computation (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/0908.3934
controlsimulationsignalingdynamicsobservationsignal propagationgeometric networksbiological cellular neural networks
Network design and communication in computer systems (68M10) Neural networks for/in biological studies, artificial life and related topics (92B20)
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Cites Work
- Unnamed Item
- Unnamed Item
- Test example for nonlinear programming codes
- A mathematical model of spontaneous calcium(II) oscillations in astrocytes
- Partial correlation analysis for the identification of synaptic connections
- Emergence of Scaling in Random Networks
- On the Use of Dynamic Bayesian Networks in Reconstructing Functional Neuronal Networks from Spike Train Ensembles
- Sequential Optimal Design of Neurophysiology Experiments
- CUTE
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