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Maximizing Lyapunov Exponents in a Chaotic Oscillator by Applying Differential Evolution

机译:通过应用微分演化最大化混沌振荡器中的Lyapunov指数

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This paper shows the application of the heuristic Differential Evolution (DE) algorithm to maximize the positive Lyapunov exponent in a third-order multi-scroll chaotic oscillator. The case of study is the saturated nonlinear function series-based chaotic oscillator. The positive Lyapunov exponent is computed for a 4-scrolls chaotic oscillator by varying the coefficients of the dynamical system (a, b, c, d(1)), in the range [0.001..1.000]. The experiments are performed and compared executing DE and a simple Genetic algorithm. The results show that DE algorithm is quite suitable to maximize the positive Lyapunov exponent of truncated coefficients over the continuous parameter spaces, because statistical studies show a small standard deviation. The comparison of the phase space diagrams of non-optimized and optimized chaotic oscillators show that for a low value of the positive Lyapunov exponent the attractor is well defined, while for its maximum value the attractor is not well appreciated, but the higher value of the exponent increases the unpredictability grade of the chaotic system.
机译:本文展示了启发式微分进化(DE)算法在最大化三阶多滚动混沌振荡器中的正Lyapunov指数中的应用。研究的案例是基于饱和非线性函数序列的混沌振荡器。通过在范围[0.001..1.000]范围内改变动力学系统的系数(a,b,c,d(1)),可以为4滚动混沌振荡器计算正Lyapunov指数。通过执行DE和简单的遗传算法进行实验并进行比较。结果表明,由于统计研究表明标准差较小,因此DE算法非常适合在连续参数空间上最大化截断系数的正Lyapunov指数。非优化和优化混沌振荡器的相空间图的比较表明,对于正Lyapunov指数的低值,吸引子得到了很好的定义,而对于最大值,吸引​​子却没有得到很好的理解,但是更高的指数增加了混沌系统的不可预测度。

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