Computer Simulation Analysis on Feature Extraction of High Speed Signal Based on Bayesian Algorithm

The discipline of journalism needs to gradually transform perspective. It combines with the characteristics of academic discourse of news communication to build a strong Chinese characteristically academic discourse system of news, so as to make a positive contribution to the development of Chinese journalism discipline. First, we analyze the general compensation model on the basis of compensation algorithm. Based on more compensation formulas, we analyze the principle of compensation. According to the basic requirements of the news communication and the unique function of Chinese characteristically academic discourse, with the basic requirements of the unique characteristics of academic discourse for news communication and Chinese characteristics, and combined with the relative reliability features extraction method of information builds academic discourse system of Chinese characteristics news communication based on Bayesian algorithm. We apply the computer to make simulation analysis on the effect of different classes' weighting factors on the system structure. The results show that the system structure has a high efficiency, good stability, and strong practicability, which has provided theoretical and technical support for the research in this field to a certain extent.