Analog circuits fault diagnosis based on multi-universe quantum neuron network

According to the uncertainty question of analogous circuit's fault diagnosis in control system, the multi-universe viewpoint which is produced based on the quantum state the superimposition phenomenon is applied to the structural design of the neural network, and a multi-universe quantum neural network model is produced. The structure system of this model include classical networks and quantum neural networks. So multi-universe quantum neural network model can use the special collapsing method to get a good diagnosis result, and also can quantify the sample structure distribution at input space. The example simulation and analysis proved that this model can more effectively solve the uncertainty problem in the fault diagnosis process compared with BP network. The model improves the fault diagnosis recognition precision greatly, and the rate of diagnosis accuracy could achieve over 95%.