WST:小波软阈值

“小波软阈值”(Wavelet Soft Thresholding,常简写为WST)是一种在信号处理与数据去噪领域广泛使用的技术,其缩写形式便于书写和交流。该方法通过对小波系数进行软阈值处理,在保留信号关键特征的同时有效抑制噪声,尤其适用于图像处理、语音分析及生物医学信号处理等综合应用场景。

Wavelet Soft Thresholding具体释义

  • 英文缩写:WST
  • 英语全称:Wavelet Soft Thresholding
  • 中文意思:小波软阈值
  • 中文拼音:xiǎo bō ruǎn yù zhí
  • 相关领域wst 未分类的

Wavelet Soft Thresholding的英文发音

例句

  1. The quality of regression was improved by combining wavelet soft thresholding with kernel partial least squares ( KPLS ).
  2. 结合小波软阈值(WST)法和核心偏最小二乘法改进回归质量。
  3. The quality of noise removal and regression was improved by combining wavelet soft thresholding with radial basis function neural network.
  4. 结合小波软阈值(WST)法和径向基函数神经网络改进了回归质量。
  5. The quality of noise removal was improved by combining wavelet soft thresholding with principal component analysis ( PCA ). HYBRID method was used for denoising, after comparison with other soft thresholding method.
  6. 该法结合小波软阈值(WST)法和主组分分析改进除噪声质量,与其它软阈值法比较选用了HYBRID法;
  7. Therefore, wavelet soft thresholding method can implement regional competition model faster.
  8. 因此,利用小波软阈值(WST)法进行区域竞争模型的数值实现效率较高。
  9. Meanwhile, with the adjustment of the speed factor, the different objects number is obtained, to satisfy various situations and requirements, which improve the application of CV model. Secondly, a numerical method based on wavelet soft thresholding for region competition model was presented.
  10. 同时,通过调整速度因子的大小,可以得到不同的目标个数,以满足不同场合和应用的需要,提高CV模型的适用范围。二、提出一种基于小波软阈值(WST)的区域竞争模型数值实现方法。