智能控制智能控制智能控制 (36).pdf
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1、Introduction Radial basis function(RBF)NN is artificial neural networks for application toproblems of supervised learning:Regression Classification Time series prediction System controlD.S.BroomheadDavid LoweLinear-separabilityNot linearly separableBasic Architecture of RBFperforms a non-linear mapp
2、ing from input space into higher dimensional spaceGaussian functionHidden layer Input layer Hidden layer Hidden units provide a set of basis function High dimensionality Output layer Linear combination of hidden functionsGaussians in RBF Gaussian Distribution Gaussian para.In RBF Gaussian centers uj
3、 Standard deviation?Alinear combination of Gaussians to approximate any function.22()()exp()2jjxuh xFinding the RBF Parameters Use the K-means algorithm to find ujOutcome:There are K clusters with means representing the centroid of each clusters.Advantages:(1)A fast and simple algorithm.(2)Reduce th
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