Context: Steady-state performance constraints for dynamical models based on RBF networks. Engineering Applications of Artificial Intelligence, vol. 20, issue 7.
ctrsim: Builds a regression matrix with symmetric RBF centers; each line corresponds to a specific center; number of columns is equal to (nu>nul) + (ny>nyl).
estimaTeta: Estimates the parameters of an RBF model using classical least squares.
estimaTeta_r: Estimates the parameters of an RBF model subject to structural constraints.
igespacocp: Defines equally spaced RBF centers according to the model's input space.
kmeans: Distributes RBF centers over data class 'x' using classical k-means.
montaP: Builds a regression matrix.
montaPsim: Builds a "symmetrical" regression matrix.
mqermod: Outputs a symmetrical weight vector using constrained least squares.
mtrsres: Builds a matrix containing constraint values of both types (symmetrical weights and symmetrical centers).
myhouse: Implements the Error Reduction Rate criterion.
simulacao: Simulates a general RBF model.
simulacao_errn: Simulates an RBF model whose structure was selected according to the ERR criterion.
simulacao_r: Simulates a structurally constrained RBF model.