The multiscale entropy assesses the complexity of a signal across different timescales. It originates from biomedical domain and was recently successfully used to characterize light curves as part supervised machine learning framework classify stellar variability. We explore behavior in detail by studying its algorithmic properties variability context linking it with traditional astronomical ti...

We develop a general framework to simultaneously exploit texture and shape characterization in multiscale image segmentation. By posing multiscale segmentation as a model selection problem, we invoke the powerful framework ooered by minimum description length (MDL). This framework dictates that multiscale segmentation comprises multiscale texture characterization and multiscale shape coding. An...

Article history: Received 8 January 2017 Accepted 27 March 2017 Available online xxxx

The objective of the paper is discussion of various methods of modelling microstructure evolution during hot forming of steels. Commonly used conventional models based on closed form equations are compared with novel approaches based on artificial neural networks (ANN) and on multiscale models. Predictive capabilities of various models are discussed. Basic principles of the ANN and multiscale m...

In the context of multiscale computations, techniques have recently been developed that enable microscopic simulators to perform macroscopic level tasks (equation-free multiscale computation). The main tool is the so-called coarse-grained time-stepper, which implements an approximation of the unavailable macroscopic time-stepper using only the microscopic simulator. Several schemes were develop...

[1] Cloud fields retrieved from remotely sensed satellite data resemble functions depicting spectral values at each spatial position (x,y). Segmenting such cloud fields through a simple thresholding technique may not provide any structurally significant information about each segmented category. An approach based on the use of multiscale convexity analysis to derive structurally significant reg...

The patchiness of zooplankton biomass for two size classes (190-600 μm and < 600 μm) as well as several environmental variables were examined in a coastal reef lagoon (Guadeloupe, French West Indies) in order to determine the mechanisms that contribute to the generation and maintenance of multiscale spatial variability in this community. A new form of multiscale analysis, called PCNM, was used ...

We perform an analysis of cardiac data using multiscale entropy as proposed in Costa et al. [Multiscale entropy analysis of complex physiological time series, Phys. Rev. Lett. 89 (2002) 068102]. We reproduce the signatures of the multiscale entropy for the three cases of young healthy hearts, atrial fibrillation and congestive heart failure. We show that one has to be cautious how to interpret ...

A recently developed multiresolution estimation framework offers the possibility of highly efficient statistical analysis, interpolation, and smoothing of extremely large data sets in a multiscale fashion. This framework enjoys a number of advantages not shared by other statistically-based methods, particularly in terms of the ability to evaluate estimates and error variances in a computational...