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NEURAL NETWORKS METHOD FOR THE LINEAR TIME VARYING SYSTEM IDENTIFICATION

This paper presents a neural network which can be used to identify linear time varying systems.The capatility of approximating linear time varying control systems on this neural network is studied.On any control functions set which is the bounded subset of L 2([0,t 1];R m),the neural network has the capatility of approximating uniform state of the linear time varying systems.We develep a new training method in which a normal orthogonal system is used as sample.After training according to this method,the output of the neural network can approximate uniform state of the linear time varying system on the subspace of L 2([0,t 1];R m) spun by this normal orthogonal system.