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Neural Network Prediction Method of Chaotic FH Code Sequence

机译:混沌FH码序列神经网络预测方法

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摘要

The frequency hopping communication implements the communication in the process of continuous and irregular jumping frequency, widely used in military communications and civilian communications. At present, the research on the modeling and prediction of frequency hopping codes by using chaos analysis and neural network and so on algorithms is very closely developed and has achieved some effects. In this paper, the RBF neural network was used to conduct simulation prediction of the m code, the RS code, and the nonlinear code these three frequency hopping codes, and the simulation experiments were carried out by MATLAB. The performance of the prediction model was analyzed and compared by theoretical analysis and simulation results. The results showed that the RBF neural network was more powerful in approximation ability, classification learning, learning speed and so on aspects.
机译:跳频通信在连续和不规则跳跃频率过程中实现了通信,广泛用于军事通信和民用通信。 目前,使用混沌分析和神经网络等频率跳频代码的建模和预测研究非常紧密地发育了一些效果。 在本文中,RBF神经网络用于对M代码,RS代码和非线性码的模拟预测进行这三个跳频码,并通过MATLAB进行模拟实验。 通过理论分析和仿真结果分析并比较了预测模型的性能。 结果表明,RBF神经网络在近似能力,分类学习,学习速度等方面更强大。

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