Generalised Recurrence Plot Analysis for Spatial Data

Abstract

Recurrence plot based methods are highly efficient and widely accepted tools for the investigation of time series or one-dimensional data. We present an extension of the recurrence plots and their quantifications in order to study recurrent structures in higher-dimensional spatial data. The capability of this extension is illustrated on prototypical 2D models. Next, the tested and proved approach is applied to assess the bone structure from CT images of human proximal tibia. We find that the spatial structures in trabecular bone become more self-similar during the bone loss in osteoporosis.

References in corpus (3)

• Recurrence Plot Based Measures of Complexity and its Application to Heart Rate Variability Data
• Comparing modern and Pleistocene ENSO-like influences in NW Argentina using nonlinear time series analysis methods
• Extended Recurrence Plot Analysis and its Application to ERP Data

Cited by in corpus (13)

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• Historical Review of Recurrence Plots
• Trends in recurrence analysis of dynamical systems
• Analysing spatially extended high-dimensional dynamics by recurrence plots
• Nonlinear interactions between the Amazon River basin and the Tropical North Atlantic at interannual timescales
• Long range node-strut analysis of trabecular bone microarchitecture
• Perturbations and Phase Transitions in Swarm Optimization Algorithms
• Extended generalized recurrence plot quantification of complex circular patterns
• Phase transitions in swarm optimization algorithms
• Quantifying Changes in the Spatial Structure of Trabecular Bone