Title :
Notice of Retraction
Evaluation of avionic system based on OLS-RBF
Author :
Kun Zhang ; Deyun Zhou
Author_Institution :
Dept. of Electron. Inf., Northwestern Polytech. Univ., Xi´an, China
Abstract :
Notice of Retraction
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
In view of UAV system development and the need of the UAV avionics system health evaluation, this paper establishes the evaluation model of avionic system state base on OLS-RBF (Ordinary Least Squares-Radial Basis Function) neural network, calculates data centers of RBF neural network by OLS algorithm to avoid the shortcomings of tradition RBF neural network. We take avionic sensor system for example, train the RBF neural network with sensor real-time data as sample, change the initial parameter setting several times, get multi-simulation results, and analyze them. The simulation result indicates that this algorithm is reasonable and effective and it can meet the requirement of real-time computing.
Keywords :
aerospace computing; avionics; computerised instrumentation; least squares approximations; radial basis function networks; OLS-RBF; UAV system development; avionic system evaluation; data centers; multisimulation results; ordinary least squares-radial basis function neural network; parameter setting; Aerospace electronics; Biological neural networks; Mathematical model; Neurons; Sensor systems; Simulation; Training; OLS-RBF; avionic system; neural network; system evaluation;
Conference_Titel :
Natural Computation (ICNC), 2011 Seventh International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-9950-2
DOI :
10.1109/ICNC.2011.6022116
