Research on Modeling of Middle Pressure Background Noise Based on Neural Network and Improved Markov Chain
In medium voltage power line communication,the channel noise composition is complex,and it needs to be analyzed and modeled separately according to different types of noise.Aiming at the background noise of a specific medium voltage line,a noise model based on wavelet packet transformation is proposed.The obtained wavelet packet coefficients are respectively trained by neural networks and the transfer probability matrix of the improved Markov chain is obtained to reconstruct the noise signals.The simulation verification and denoising are carried out,and the two methods are compared with the traditional direct neural network training.The results show that the noise built by the improved Markov chain method is more accurate than the traditional Markov chain method.The noise built by the neural network method based on the wavelet packet transform is more similar to the original noise,and the noise reduction effect is better than that of the traditional neural network training method,which provides a feasible scheme for the further study of medium voltage power line communication.
medium voltage power line communicationwavelet packet transformneural networkMarkov chain
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