The Application Of Wavelet Neural Network In Nonlinear Identification

Although the use of traditional identification methods as Impulse response andleast-square procedure are sophisticated, point to the object with obvious nonlinearcharacteristic, it is difficult to describe the characteristic of object. The identification ofobject is easy to trap in local minimum, Radical basic Function network ,because therelation between network and output is linear, so we can adopt the method which assureglobal convergence and get the globally optimal solution, but it is difficult to choose thecenter point .So point to the election of the mode and structure, the article presents aalgorithm of wavelet network, using the algorithm to train the network, after then used tothe practical nonlinear system. Experimental results show that wavelet network aftertraining is able to obtain better result, and the network scope is small, it can be therationalization mode of the practical system.