自适应模糊神经网络MATLAB代码

function c sigma W output SOFNN X d Kd SOFNN Self Organizing Fuzzy Neural Networks Input Parameters X r n rth traning data from nth observation d n the desired output of the network must be a row vector Kd r predefined distance threshold for the rth input Output Parameters c IndexInputVariable IndexNeuron sigma IndexInputVariable IndexNeuron W output is a vector Setting up Parameters for SOFNN SigmaZero 4 delta 0 12 threshold 0 1354 k sigma 1 12 For more accurate results uncomment the following format long Implementation of a SOFNN model size R size N size X size R the number of input variables c sigma W output u 0 the number of neurons in the structure Q O Psi for n 1 size N x X n if u 0 No neuron in the structure c x sigma SigmaZero ones size R 1 u 1 Psi GetMePsi X c sigma Q O UpdateStructure X Psi d pT n GetMeGreatPsi x Psi n else Q O pT n UpdateStructureRecursively X Psi Q O d n end KeepSpinning true while KeepSpinning Calculate the error and if part criteria ae abs d n pT n O approximation error phi GetMePhi x c sigma maxphi maxindex max phi maxindex refers to the neuron s index if ae delta if maxphi threshold enlarge width minsigma minindex min sigma maxindex sigma minindex maxindex k sigma minsigma Psi GetMePsi X c sigma Q O UpdateStructure X Psi d pT n GetMeGreatPsi x Psi n else Add a new neuron and update structure ctemp sigmatemp dist 0 for r 1 size R dist abs x r c r 1 distIndex 1 for j 2 u if abs x r c r j dist distIndex j dist abs x r c r j end end if dist Kd r ctemp ctemp c r distIndex sigmatemp sigmatemp sigma r distIndex else ctemp ctemp x r sigmatemp sigmatemp dist end end c c ctemp sigma sigma sigmatemp Psi GetMePsi X c sigma Q O UpdateStructure X Psi d KeepSpinning false u u 1 end else if maxphi ae L Q p n temp 1 Q next eye length Q L pT n Q O next O L ee else Q next eye length Q Q O next O end end function Q O UpdateStructure X Psi d GreatPsiBig GetMeGreatPsi X Psi M u r 1 n the number of observations M size GreatPsiBig Others Ways of getting Q P T t P t 1 opts SYM true Q linsolve GreatPsiBig GreatPsiBig eye M opts Q inv GreatPsiBig GreatPsiBig Q pinv GreatPsiBig GreatPsiBig Y GreatPsiBig eye M Q GreatPsiBig Y O Q GreatPsiBig d end This function works too with x X X and Psi is a Matrix Gets you the whole GreatPsi X x and Psi is the row related to x Gets you just the column related with the observation function GreatPsi GetMeGreatPsi X Psi Psi In a row you go through the neurons and in a column you go through number of observations Psi obs IndexNeuron GreatPsi N U size Psi for n 1 N x X n GreatPsiCol for u 1 U GreatPsiCol GreatPsiCol Psi n u 1 x end GreatPsi GreatPsi GreatPsiCol end end function phi SumPhi GetMePhi x c sigma r u size c u the number of neurons in the structure r the number of input variables phi SumPhi 0 for j 1 u moving through the neurons S 0 for i 1 r moving through the input variables S S x i c i j 2 2 sigma i j 2 end phi phi exp S SumPhi SumPhi phi j phi u exp S end end This function works too with x it will give you the row related to x function Psi GetMePsi X c sigma u size c size N size X u the number of neurons in the structure size N the number of observations Psi for n 1 size N phi SumPhi GetMePhi X n c sigma PsiTemp for j 1 u PsiTemp is a row vector ex