Application of Sfg in Learning Algorithms of Neural Networks
نویسندگان
چکیده
The paper presents application of signal ow graphs SFG and adjoint ow graphs AFG in determination of gradient vector for feedforward neural networks The presented approach is universal and applicable in the same form irrespective of the particular structure of the network The applicability of the method has been shown on the example of di erent types of neural networks multilayer perceptron sigma pi network generalized radial basis network and multilayer Volterra network It nds application in any gradient based learning algorithms of neural networks Some applications of this method concerning the prediction and identi cation of the nonlinear dynamic plants are presented and discussed in the paper
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