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针对有界噪声激励下Hénon-Heiles系统响应的杂乱特性,通过改进一类降噪算法,给出经降噪算法处理后响应的重构特征及相应最大Lyapunov指数.结果表明:经改进后的算法在处理Hénon映射的含测量噪声的混沌吸引子时更为有效;有界噪声激励使Hénon-Heiles系统的样本响应远离无噪声时的确定轨迹,但经过改进的降噪算法处理后的重构相图能体现出确定情形下系统的固有特性;可利用这一改进算法对杂乱输出信号进行混沌特征提取与分析;在系统无法避免噪声激励干扰的情况下,主动地适度增加随机激励的强度可能会得到更好的混沌特性识别效果.
Aiming at the chaotic characteristic of Hénon-Heiles system under bounded noise excitation, a modified denoising algorithm is proposed to obtain the reconstructed characteristics and the corresponding maximum Lyapunov exponent after the noise reduction processing. The results show that the improved algorithm It is more effective when dealing with Hénon-mapped chaotic attractors with measurement noise. Bounded noise excitations make the Hénon-Heiles system’s sample response far away from the deterministic trajectory without noise, but the reconstructed phase after the improved noise reduction algorithm The map can reflect the inherent characteristics of the system under certain circumstances. The improved algorithm can be used to extract and analyze the chaotic features of the cluttered output signal. If the system can not avoid the noise excitation interference, it may be possible to increase the intensity of the random excitation moderately and proactively Get better recognition of chaotic characteristics.