双模噪声背景下自适应小波阈值去噪

在分析双模噪声模型统计特性的基础上提出自适应小波阈值算法。新算法中设计改进的阈值函数和控制函数，克服了传统硬、软阈值法的不足，并且自适应得到最佳控制因子。该算法对加入双模噪声的信号进行闭环反馈处理：小波分解、阈值量化处理、小波逆变换重构信号、控制函数寻优。Matlab 2012a仿真结果表明，该算法相对于传统硬、软阈值法，去噪图形曲线清晰、光滑、连续性好，信噪比分别提高9 dB和4 dB。在双模噪声背景下，自适应小波阈值去噪有效、可行，拓展了小波阈值算法的应用。

Adaptive wavelet threshold denoising under dual-mode noise background

An adaptive wavelet threshold algorithm is put forward through analyzing the statistical characteristics of dual-mode noise model.In the new algorithm,improved threshold function and control function are proposed to overcome the deficiency of the traditional hard and soft threshold method,and get the optimal control factor adaptively. The algorithm performs following closed-loop feedback processing of signal in which dual-mode noise is added :wavelet decomposition and threshold quantization processing,wavelet inverse transformation to reconstruct signal,and control function optimization. Matlab 2012a simulation results show that the denoising graph curve is clear,smooth and in good continuity,and the signal-to-noise ratio(SNR) is improved 9 dB and 4 dB,respectively.Under the background of dual-mode noise,adaptive wavelet threshold denoising is effective and feasible,and it extends the application of the wavelet threshold algorithm.