Complexity analysis of the time series using inverse dispersion entropy

Nonlinear Dynamics - The primary object of this study is to measure the complexity of different types of signals. We undertake the experiment to support the hypothesis of inverse dispersion entropy...     

离散的Painlevé方程Ⅱ的有理解

§１．　ＩｎｔｒｏｄｕｃｔｉｏｎＮｏｎｌｉｎｅａｒｉｎｔｅｇｒａｂｌｅｄｉｓｃｒｅｔｅｓｙｓｔｅｍｓａｒｅｎｏｗａｔｔｒａｃｔｉｎｇｍｕｃｈａｔｔｅｎｔｉｏｎ．Ａｍｏｎｇｔｈｅｍ,ｔｈｅｄｉｓｃｒｅｔｅＰａｉｎｌｅｖéｅｑｕａｔｉｏｎｓａｒｅｅｘｐｅｃｔｅｄｔｏｂｅｔｈｅｍｏｓｔｆｕｎｄａｍｅｎｔａｌｏｎｅｓｉｎａｎａｌｏｇｙｔｏｔｈｅｃｏｎｔｉｎｕｏｕｓｃａｓｅ．Ｃｌｏｓｅｒｓｔｕｄｉｅｓａｒｅｈｏｗｒｅｖｅａｌｉｎｇｔｈｅｉｒｒｉｃｈｍａｔｈｅｍａｔｉｃａｌｓｔｒｕｃｔｕｒｅｓ,ｓｕｃｈａｓ…     

Improved electrochemical performance of NaAlO2-coated LiCoO2 for lithium-ion batteries

Journal of Solid State Electrochemistry - NaAlO2-coated LiCoO2 materials have been synthesized as cathode materials for lithium-ion batteries. The NaAlO2 layer is coated on the LiCoO2 particles...     

Measuring the asymmetric contributions of individual subsystems

Information on the structure of a complex system can be obtained by measuring at what rate the individual subsystems exchange information among each other and to what extent they contribute to the information production. In this paper, we use relative transfer entropy to analyze the contributions of asymmetric information flow from one subsystem to another. We also propose information-theoretic tools to estimate the contributions of individual subsystems to the information production of system over time. On one hand, we analyze the artificial processes, including unidirectionally coupled linear processes, unidirectionally coupled Rössler systems, and bidirectionally coupled Hénon maps that reveal the information flows between variables and the contributions to the information production of each variable. On the other hand, we apply these measures to real-world systems, the stock markets that uncover the interactions between high-frequency stock price and trading volume.