Strobl C, Ott L, Kaiser J, Gosses K, Schäfer M, Rabenstein R (2018)
Publication Language: English
Publication Type: Conference contribution, Conference Contribution
Publication year: 2018
Event location: Albuquerque, NM USA
DOI: 10.1109/holm.2018.8611739
This paper considers particle propagation in a cylindrical molecular
communication channel, e.g. a simplified model of a blood vessel.
Emitted particles are influenced by diffusion, flow, and a vertical
force induced e.g. by gravity or magnetism. The dynamics of the diffusion
process are modeled by multi-dimensional transfer functions
in a spatio-temporal frequency domain. Realistic boundary conditions
are incorporated by the design of a feedback loop. The result is
a discrete-time semi-analytical model for the particle concentration.
The model is validated by comparison to particle-based simulations.
These numerical experiments reveal that the particle concentration
of the proposed semi-analytical model and the particle-based model
are in excellent agreement. The analytical form of the proposed
solution provides several benefits over purely numerical models, e.g.
high variability, existence of low run-time algorithms, extendability
to several kinds of boundary conditions, and analytical connection
to parameters from communication theory.
APA:
Strobl, C., Ott, L., Kaiser, J., Gosses, K., Schäfer, M., & Rabenstein, R. (2018). Refined Fault Detection in LVDC-Grids with Signal Processing, System Identification and Machine Learning Methods. In Proceedings of the 29th International Conference on Electrical Contacts, Together with 64th IEEE Holm Conference on Electrical Contacts. Albuquerque, NM USA, US.
MLA:
Strobl, Christian, et al. "Refined Fault Detection in LVDC-Grids with Signal Processing, System Identification and Machine Learning Methods." Proceedings of the 29th International Conference on Electrical Contacts, Together with 64th IEEE Holm Conference on Electrical Contacts, Albuquerque, NM USA 2018.
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