基于神經(jīng)模糊推理系統(tǒng)的混沌序列產(chǎn)生模型
A Chaotic Sequence Generation Model Based on ANFIS
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摘要: 結(jié)合神經(jīng)網(wǎng)絡(luò)和模糊系統(tǒng)兩者的優(yōu)點，首次提出并建立了基于自適應(yīng)神經(jīng)模糊推理系統(tǒng)的混沌序列產(chǎn)生模型，其中系統(tǒng)適配參數(shù)的搜索運用遺傳算法來實現(xiàn)。對該模型產(chǎn)生的混沌序列相關(guān)性、平衡性進(jìn)行了檢驗。結(jié)果表明，其性能均達(dá)到或優(yōu)于由混沌映射直接產(chǎn)生的混沌序列，且具有很高的復(fù)雜度，適合作為擴頻通信應(yīng)用的偽隨機碼。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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