基于蜂群算法和新阈值函数的信号去噪算法

Signal denoising method based on bee colony algorithm and new threshold function

针对阈值和阈值函数的调节参数取值问题,提出一种基于人工蜂群优化算法的带参新阈值函数的信号去噪算法。首先,验证带参新阈值函数的连续性、高阶可微性、参数可调性;其次,根据最小均方误差(MSE)策略,利用人工蜂群优化算法优化各分解层的阈值和调整参数,得到最优去噪信号;最后,利用信噪比(SNR)、MSE指标验证信号的去噪效果。实验结果表明,人工蜂群优化算法选取的阈值参数和新小波阈值函数可以有效地对带噪信号去噪。

Aiming at the problems of selecting the adjustment parameters in threshold and threshold function,this paper proposed a signal denoising method based on artificial bee optimization algorithm and new threshold function.Firstly,it carried out the theoretical analysis of the new threshold function to verify its continuity,high-order differentiability and parameter adjustability.Secondly,according to the minimum mean square error(MSE)strategy,it used the artificial bee colony optimization algorithm to optimize the thresholds and adjustment parameters of each decomposition layer,and then obtained the optimal denoised signal.Finally,it carried out the simulation experiment to verify the denoising effect according to the signal-to-noise ratio(SNR)and MSE.The experimental result shows that the threshold parameters selected by artificial bee optimization algorithm and the new wavelet threshold function can effectively denoise a noisy signal.