A fuzzy entropy based noisy signal processing method and an iterative singular spectrum analysis (SSA) soft threshold de-noising method are disclosed. The method employs FuzzyEn, which is used to quantify the system complexity in chaos theory, to characterize a noise floor, which provides a more effective path for processing of noisy signal; its fuzzy entropy spectrum based iterative singular spectrum analysis soft threshold (SSA-IST) de-noising method outperforms the conventional truncated singular spectrum, wavelet transform and empirical mode decomposition de-noising approaches in de-noising performance.

A fuzzy entropy based noisy signal processing method and an iterative singular spectrum analysis (SSA) soft threshold de-noising method are disclosed. The method employs FuzzyEn, which is used to quantify the system complexity in chaos theory, to characterize a noise floor, which provides a more effective path for processing of noisy signal; its fuzzy entropy spectrum based iterative singular spectrum analysis soft threshold (SSA-IST) de-noising method outperforms the conventional truncated singular spectrum, wavelet transform and empirical mode decomposition de-noising approaches in de-noising performance.