Distinguishing Noise from Chaos

作     者：O. A. Rosso H. A. Larrondo M. T. Martin A. Plastino M. A. Fuentes 

作者机构：Centre for Bioinformatics Biomarker Discovery and Information-Based Medicine School of Electrical Engineering and Computer Science The University of Newcastle University Drive Callaghan NSW 2308 Australia Instituto de Cálculo Facultad de Ciencias Exactas y Naturales Universidad de Buenos Aires 1428 Ciudad Universitaria Buenos Aires Argentina Facultad de Ingeniería Universidad Nacional de Mar del Plata Juan B. Justo 4302 7600 Mar del Plata Argentina Instituto de Física Facultad de Ciencias Exactas Universidad Nacional de La Plata C.C. 727 1900 La Plata Argentina Santa Fe Institute 1399 Hyde Park Road Santa Fe New Mexico 87501 USA Instituto Balseiro Centro Atómico Bariloche and CONICET 8400 Bariloche Argentina 

出 版 物：《Physical Review Letters》 (Phys Rev Lett)

年 卷 期：2007年第99卷第15期

页      面：154102-154102页

核心收录：

学科分类：07[理学] 0702[理学-物理学] 

主　　题：Acoustic noise 

摘      要：Chaotic systems share with stochastic processes several properties that make them almost undistinguishable. In this communication we introduce a representation space, to be called the complexity-entropy causality plane. Its horizontal and vertical axis are suitable functionals of the pertinent probability distribution, namely, the entropy of the system and an appropriate statistical complexity measure, respectively. These two functionals are evaluated using the Bandt-Pompe recipe to assign a probability distribution function to the time series generated by the system. Several well-known model-generated time series, usually regarded as being of either stochastic or chaotic nature, are analyzed so as to illustrate the approach. The main achievement of this communication is the possibility of clearly distinguishing between them in our representation space, something that is rather difficult otherwise.