KEYWORDS: Signal processing, Design, Digital signal processing, Field programmable gate arrays, Telecommunications, Control systems, Data transmission, Analog electronics, Wireless communications, Antennas
This study first describes the application and development level of software defined radio; Secondly, it analyzes the problems of traditional radio and the advantages of software defined radio. Again, several software defined radio platforms based on different signal processors are discussed and compared in terms of performance and application. Finally, the text transmission system of software radio platform based on FPGA (Field Programmable Gate Array) is designed in detail, and text data sending and receiving are realized.
As a new generation of electrical insulation medium, SF6 gas is widely used in electrical insulation and arc extinguishing in high-voltage power equipment-Therefore, the accuracy of its concentration measurement is very important, which has an important impact on improving the performance and safety of power equipment. The paper elaborates particle swarm optimization (PSO) algorithm combining the application effect of radial basis function (RBF) network and backpropagation (BP) network in predicting sulfur hexafluoride (SF6) gas concentration prediction. In order to avoid the factors of insufficient data and obvious data characteristics, a large number of data sets with different trends are randomly generated for model verification. The performance of the two methods is verified experimentally, and the results show that the PSO-RBF method performs better in predicting SF6 gas concentration, by which the changes of the gas concentration can be predicted more accurately, and shows robustness for prediction under different conditions. In addition, the PSO-RBF method converges faster in the training of temperature compensation model, which improves the efficiency of the prediction model. It has practical application value for the prediction and monitoring of power equipment, and also provides new solutions for other similar gas prediction problems.
The continuous development of network accounting has promoted the continuous improvement of accounting operation means, objectives, functions, and supervision and management of enterprises. However, it cannot be ignored that network technology has also brought serious security threats to accounting information system. This article mainly conducts research on network accounting information security based on classification and regression tree algorithm. This article first introduces the security risks of network accounting information, then analyzes the principle of decision trees and the selection of classifiers. Finally, this article uses classification and regression trees to construct a network accounting information security model. Through the experimental results, it can be concluded that the network accounting information security model has a recognition rate of 90.33% for accounting information, which is superior to most information security models.
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