小波阈值去噪算法在信号处理中的应用与优化

Application and Optimization of Wavelet Threshold De-nosing Method in Signal Processing

小波阈值方法通过预先对数据奇异值的剔除进行信号滤波.在传统的硬阈值和软阈值方法基础上,提出了一种新的阈值函数,该函数具有更优越的数学特性和清晰的物理意义.能够精确地剔除信号中的噪声,有效地提取出信号的主要部分和细节部分.通过仿真实验,证明该函数更好地解决了信号处理中数据奇异值和系统随机误差问题,提高了数据处理的精度和效率,是一种比较有效的信号消噪方法,在信号处理领域具有广阔的工程应用价值.

Wavelet threshold method eliminates strange data in advance to filter signal. Based on the tra- ditional soft-threshold method and hard-threshold method, a new threshold function is put forward, which is more excellent in mathematic characteristics and physical meanings. This new function can eliminate the noise in signals accurately to extract signals more effectively. Simulation results show that the new function is more superior in eliminating strange data and reducing system random error in signal processing, which will improve signal processing accuracy and efficiency. As an effective signal de-noising method, it will have a broad application in signal processing area.