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Denoising Nonlinear Time Series Using Singular Spectrum Analysis and Fuzzy Entropy 被引量:1
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作者 江剑 谢洪波 《Chinese Physics Letters》 SCIE CAS CSCD 2016年第10期19-23,共5页
We present a hybrid singular spectrum analysis (SSA) and fuzzy entropy method to filter noisy nonlinear time series. With this approach, SSA decomposes the noisy time series into its constituent components including... We present a hybrid singular spectrum analysis (SSA) and fuzzy entropy method to filter noisy nonlinear time series. With this approach, SSA decomposes the noisy time series into its constituent components including both the deterministic behavior and noise, while fuzzy entropy automatically differentiates the optimal dominant components from the noise based on the complexity of each component. We demonstrate the effectiveness of the hybrid approach in reconstructing the Lorenz and Mackey--Class attractors, as well as improving the multi-step prediction quality of these two series in noisy environments. 展开更多
关键词 of on or in Denoising Nonlinear Time series Using singular Spectrum Analysis and Fuzzy Entropy NLP IS
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The Most Likely Common Difference of Arithmetic Progressions Among Primes
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作者 Xiaosheng Wu Pengzhen Yang 《Communications in Mathematics and Statistics》 SCIE 2021年第3期315-329,共15页
Let d^(∗)_(k)(x)be the most likely common differences of arithmetic progressions of length k+1 among primes≤x.Based on the truth of Hardy–Littlewood Conjecture,we obtain that lim x→+∞d^(∗)_(k)(x)(x)=+∞uniformly i... Let d^(∗)_(k)(x)be the most likely common differences of arithmetic progressions of length k+1 among primes≤x.Based on the truth of Hardy–Littlewood Conjecture,we obtain that lim x→+∞d^(∗)_(k)(x)(x)=+∞uniformly in k,and every prime divides all sufficiently large most likely common differences. 展开更多
关键词 Common difference Arithmetic progression Hardy–Littlewood Conjecture Differences among primes singular series
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