变形序列小波消噪最佳分解尺度量化指标的确定
)To Determine the Quantitative Index for the Optimal Decomposition Scalein Wavelet De-noising of Deformation Series
-
摘要: 目的 小波消噪分解尺度确定的正确与否,直接关系到消噪效果。针对变形序列的消噪,将时序分析建模定价的信息准则与高斯白噪声在小波变换下的特性相结合,提出了用 Akaike信息准则作为量化指标,确定小波消噪最佳分解尺度的方法。模拟数据和工程数据的验证结果表明,在 Akaike信息准则计算值达到最小时,所确定的分解尺度符合信噪分布规律,达到了较好的消噪效果,实现了作为小波消噪最佳分解尺度确定的量化指标作用,提升了小波消噪在变形数据处理中应用的便捷性。Abstract: Objective Wavelet decomposition scale is directly related to the effect of de-noising.To de-noising ofdeformation sequence,the authorcombines the information criterion of the time series analysis model-ing pricing and the characteristics of Gauss white noise under the wavelet transform,put forward themethod thatthe Akaike information criterion was used as quantitativeindex to determine the optimaldecomposition scale.The calculation results of examples show that in the Akaike information criterioncalculated value to the Minimum,the decomposition scale determinedconform to the distribution of sig-nal-to-noise,de-noising effect is better,and Akaike information criterion was used as quantitative in-dex to determine the optimal decomposition scale is effective,itimprove the convenience of wavelet de-noising in deformation data processing.
下载:
