基于神经模糊推理系统的混沌序列产生模型
A Chaotic Sequence Generation Model Based on ANFIS
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摘要: 结合神经网络和模糊系统两者的优点，首次提出并建立了基于自适应神经模糊推理系统的混沌序列产生模型，其中系统适配参数的搜索运用遗传算法来实现。对该模型产生的混沌序列相关性、平衡性进行了检验。结果表明，其性能均达到或优于由混沌映射直接产生的混沌序列，且具有很高的复杂度，适合作为扩频通信应用的伪随机码。Abstract: In this paper, combining both neural networks and fuzzy systems merits, a chaotic sequence generation model is proposed and constructed on the basis of Adaptive Neural Fuzzy Inference System(ANPIS) firstly. Its basic system parameters are adjusted by genetic algorithm. The correlation property and balance performance of chaotic sequences generated by this model is tested. The result shows performances of these chaotic sequences are as good as, or better than that of chaotic sequences directly by chaotic map, which possess very high complexity and suit to act as spread-spectrum communication applications pseudo code.
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