Abstract

Communication system diagnosis by the embedded passive low-pass filter and SVM is proposed in this paper. Then, we perfom the experimental study for communication system diagnosis by the embedded passive low-pass filter and SVM. A parallel port communication system is employed to study the communi-cation system diagnosis ability by the embedded passive low-pass filter and SVM.The samples collected by the experiments are processed by the embedded passive low-pass filter. Firstly, we use the embedded passive low-pass filter and SVM to perform the diagnosis for parallel port communication system, it can be seen that the number of incorrect diagnosis of the embedded passive low-pass filter and SVM is only 2. Then, we use RBF neural network, BP neural network to perform the diagnosis for parallel port communication system respectively. The experimental results indicate that the diagnosis ability for parallel port communication system of the embedded passive low-pass filter and SVM is better than that of RBF neural network and BP neural network.

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