基于数学形态学的自适应余弦拟合随机共振幅值估计研究

Stochastic Resonance Amplitude Estimation of Adaptive Cosine Fitting Based on Mathematical Morphology

针对余弦拟合算法计算量大、准度不高等问题,本文基于数学形态学对频域进行平滑处理,提出一种对特定频率峰值拟合的自适应参数调节随机共振幅值估计算法。首先,利用移频变尺度线性压缩随机共振检测出特定频率并利用所得频率设计出余弦曲线,在此基础上基于数学形态学对特定频率进行平滑处理,提出一种以特定频率的峰值为拟合目标的自适应参数调节方法,从而实现微弱信号的幅值估计。通过仿真数据,证明该算法比余弦拟合算法有效率,精度提升了1.33%。

Aiming at the problem thatthe cosine fitting algorithm is large and the accuracy is not high, this paper proposes a kind of adaptive parameter adjustment of Stochastic Resonance Amplitude Estimation with fitting spe_ ciflc frequency for the peak frequency based on mathematical morphology. Firstly, the specific frequency is detected by Scale-transformation theory and the cosine curve is designed by using the obtained frequency. With mathematical morphology processing spectrum, an adaptive parameter adjustment method w ith the peak of a specific frequency as the fitting target is proposed to achieve the amplitude of the weak signal. Through the simulation data, it is proved that the algorithm is more efficient than the cosine fitting algorithm, and the precision is improved by 1.33%.