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Detection and characterization of dynamical heterogeneity in an event series using wavelet correlation

机译:使用小波相关性检测和表征事件序列中的动态异质性

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摘要

A method that combines wavelet-based multiscale decomposition with correlation statistical analysis to extract, detect, and characterize time-dependent variations in the spectral response of a system has been developed. The approach is independent of the distribution of the observable and does not rely on any presumed kinetic model for the system's dynamical response. It provides a quantitative and objective framework for studies of complex systems exhibiting dynamics that are nonuniform in time. Applying this method to computer simulated data, it is shown that the wavelet correlation approach is capable of resolving the size fluctuations in a single nanostructure by single-molecule tracking spectroscopy. (C) 2008 American Institute of Physics.
机译:已经开发了一种将基于小波的多尺度分解与相关统计分析相结合,以提取,检测和表征系统的光谱响应中随时间变化的方法。该方法独立于可观测对象的分布,并且不依赖于系统动力学响应的任何假定动力学模型。它为研究动态时间不均匀的复杂系统提供了定量和客观的框架。将这种方法应用于计算机模拟数据,表明小波相关方法能够通过单分子跟踪光谱技术解决单个纳米结构中的尺寸波动。 (C)2008美国物理研究所。

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