The Application of RBF Neural Networks in Curve Fitting

Abstract:

Three means to realize function approach such as the interpolation approach, fitting approach as well as the neural network approach are discussed based on Matlab to meet the demand of data processing in engineering application. Based on basic principle of introduction, realization methods to non-linear are researched using interpolation function and fitting function in Matlab with example. It mainly studies the RBF neural networks and the training method. RBF neural network to proximate nonlinear function is designed and the desired effect is achieved through the training and simulation of network. As is shown from the simulation results, RBF network has strong nonlinear processing and approximating features, and RBF network model has the characteristics of high precision, fast learning speed for the prediction.

• Periodical: Advanced Materials Research (Volumes 490-495)
• Pages: 688-692
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.490-495.688
• Online since: March 2012
• Authors: Zhong Biao Sheng, Xiao Rong Tong
• Keywords: Curve Fitting, MATLAB, RBF Neural Network

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