摘要
提出一种分维数和子波重构相结合的混沌信号与噪声分离方法，与以往出现的子波滤波方法和经典滤波方法相比较，该方法有如下特点：利用子波变换计算带观测噪声混沌信号的真实分数维，进而根据观测序列维数与真实维数的差值控制子波重构的参数，构造出混沌与噪声分离的自适应滤波器结构。仿真实验说明了该算法的有效性。
A novel adaptive noise reduction method for chaotic signals based on wavelet reconstruction and fractal theory is presented. Compared with traditional methods and wavelet filtration method, the property of the method is: the actual fractal dimension of chaotic signal with noises is estimated by the wavelet transformation, and then the wavelet reconstruction parameter can be controlled in accordance with the deviation of the observed sequence dimension from the actual dimension to construct an adaptive filter structure. The simulation results demonstrate that the algorithm is fairly good in performance.
出处
《南京航空航天大学学报》
EI
CAS
CSCD
北大核心
1997年第5期483-487,共5页
Journal of Nanjing University of Aeronautics & Astronautics
基金
国家自然科学基金
航空科学基金
关键词
混沌
噪声
分数维
子波重构
分形内插
信号处理
chaos
noise
fractal dimension
wavelet reconstruction
fractal interpolation
