On Training Algorithms of Flexible Neural Networks

To the problem that flexible neural networks is a kind of network structure with high flexibility,but the training algorithms is not so rich compared with classic neural networks,using matrix as the basic arithmetic unit,the steepest descent algorithm and LM optimization algorithm are deduced.With matrix being used as the basic arithmetic unit,highly efficient LAPACK can be applied to deal with programming,which shall increase the accuracy and speed of numerical computation.Finally,a simulation example shows the validity of the algorithm,and indicates that flexible neural network,to a certain degree,overcomes the disadvantages of classic BP network training.