关键词: 小波方差分解, 混沌, 噪声估计, 噪声平滑, 阈值方法, 股票市场, 期货市场

Abstract: In wavelet noise processing, signal decomposition catches more attention while noise itself is ignored. To solve this problem, by using the function of wavelet variance decomposition to analyze white noise, a new method of noise estimation and reduction by thresholding was proposed for chaotic time series. The noise level was estimated with wavelet variances at first and second scale, while the soft threshold was chosen by calculating wavelet variance of noise at every scale. The method was tested in Lorenz and Chen's system. The result shows that the proposed method is better than other wavelet noise estimation and reduction methods. At last, it is proved to be effective in de-noising Shanghai Stock Exchange (SSE) index and Shanghai Futures Exchange (SHFE) rubber futures time series.

Key words: wavelet variance decomposition, chaos, noise estimation, noise smoothing, thresholding, stock market, futures market