Calibration of nonlinear variable loads based on manifold learning
In this work, we present a method for calibrating non-linear variable impedances based on the manifold-learning technique. This approach circumvents the dependency on the analytical model of the device, and works under the assumption that the impedance values come from a ”black box” controlled by a...
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| Formato: | Objeto de conferencia |
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2017
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| Acceso en línea: | http://sedici.unlp.edu.ar/handle/10915/154145 |
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I19-R120-10915-1541452023-06-09T04:07:31Z http://sedici.unlp.edu.ar/handle/10915/154145 isbn:978-987-544-754-7 Calibration of nonlinear variable loads based on manifold learning Venere, Alejandro Javier Hurtado, Martín Muravchik, Carlos Horacio 2017-09 2017 2023-06-08T17:36:28Z en Ingeniería Diffusion map Manifold learning Variable loads In this work, we present a method for calibrating non-linear variable impedances based on the manifold-learning technique. This approach circumvents the dependency on the analytical model of the device, and works under the assumption that the impedance values come from a ”black box” controlled by a number of independent parameters. The goal of the calibration is to recover the unknown control parameters that set the load into the desired impedance states. We tested the proposed procedure first on a simulated example and then on the prototype presented in [1] at a frequency of 1575.42 MHz. The results based on both simulated and real data showed accurate recovery of the control parameters. Instituto de Investigaciones en Electrónica, Control y Procesamiento de Señales Objeto de conferencia Objeto de conferencia http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) application/pdf |
| institution |
Universidad Nacional de La Plata |
| institution_str |
I-19 |
| repository_str |
R-120 |
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SEDICI (UNLP) |
| language |
Inglés |
| topic |
Ingeniería Diffusion map Manifold learning Variable loads |
| spellingShingle |
Ingeniería Diffusion map Manifold learning Variable loads Venere, Alejandro Javier Hurtado, Martín Muravchik, Carlos Horacio Calibration of nonlinear variable loads based on manifold learning |
| topic_facet |
Ingeniería Diffusion map Manifold learning Variable loads |
| description |
In this work, we present a method for calibrating non-linear variable impedances based on the manifold-learning technique. This approach circumvents the dependency on the analytical model of the device, and works under the assumption that the impedance values come from a ”black box” controlled by a number of independent parameters. The goal of the calibration is to recover the unknown control parameters that set the load into the desired impedance states. We tested the proposed procedure first on a simulated example and then on the prototype presented in [1] at a frequency of 1575.42 MHz. The results based on both simulated and real data showed accurate recovery of the control parameters. |
| format |
Objeto de conferencia Objeto de conferencia |
| author |
Venere, Alejandro Javier Hurtado, Martín Muravchik, Carlos Horacio |
| author_facet |
Venere, Alejandro Javier Hurtado, Martín Muravchik, Carlos Horacio |
| author_sort |
Venere, Alejandro Javier |
| title |
Calibration of nonlinear variable loads based on manifold learning |
| title_short |
Calibration of nonlinear variable loads based on manifold learning |
| title_full |
Calibration of nonlinear variable loads based on manifold learning |
| title_fullStr |
Calibration of nonlinear variable loads based on manifold learning |
| title_full_unstemmed |
Calibration of nonlinear variable loads based on manifold learning |
| title_sort |
calibration of nonlinear variable loads based on manifold learning |
| publishDate |
2017 |
| url |
http://sedici.unlp.edu.ar/handle/10915/154145 |
| work_keys_str_mv |
AT venerealejandrojavier calibrationofnonlinearvariableloadsbasedonmanifoldlearning AT hurtadomartin calibrationofnonlinearvariableloadsbasedonmanifoldlearning AT muravchikcarloshoracio calibrationofnonlinearvariableloadsbasedonmanifoldlearning |
| _version_ |
1768268593613504512 |