Analysis of the Temporal Structure Evolution of Physical Systems with the Self-Organising Tree Algorithm (SOTA): Application for Validating Neural Network Systems on Adaptive Optics Data before On-Sky Implementation

Entropy

Francisco Javier Iglesias Rodríguez¹  Francisco Javier de Cos Juez²  Sergio Luis Suárez Gómez²  Jesús Daniel Santos Rodríguez³ 

[1] Departamento de Administración de Empresas, Universidad de Oviedo, Avenida de El Cristo s/n, 33071 Oviedo, Spain;Departamento de Explotación y Prospección de Minas, University of Oviedo, Independencia 13, 33004 Oviedo, Spain;Departamento de Física, Universidad de Oviedo, Calvo Sotelo s/n, 33007 Oviedo, Spain;

关键词: Artificial Neural Networks;    time series clustering;    adaptive optics;   

DOI  :  10.3390/e19030103

来源: DOAJ

【 摘 要 】

Adaptive optics reconstructors are needed to remove the effects of atmospheric distortion in optical systems of large telescopes. The use of reconstructors based on neural networks has been proved successful in recent times. Some of their properties require a specific characterization. A procedure, based in time series clustering algorithms, is presented to characterize the relationship between temporal structure of inputs and outputs, through analyzing the data provided by the system. This procedure is used to compare the performance of a reconstructor based in Artificial Neural Networks, with one that shows promising results, but is still in development, in order to corroborate its suitability previously to its implementation in real applications. Also, this procedure could be applied with other physical systems that also have evolution in time.

【 授权许可】

Unknown