The current recognition algorithms of communication signals often have high complexity and poor anti-noise performance. To this problem, the paper proposed a communication signal modulation identification algorithm, which is based on fractal box dimension and index entropy. This paper first extracts box counting dimension characteristics of signals which characterize signals’ complexity to clas...

Theoretical advances toward a purely meshless framework for analysis of the generalized fractal dimension, with applications to turbulence, are considered. The key basic theoretical idea is the formulation of the probability density function of the minimum distance to the nearest part of the flow feature of interest, e.g. a turbulent interface, from any location randomly chosen within a referen...

In this paper, a new box-counting method to achieve highly specific topological fingerprinting of architecture in relation the position observer and context its surroundings is proposed. Central use 360-degree spherical panoramas as basis for fractal measurement. Thus, number problems comparative analysis dimension field are explicitly implicitly addressed, first foremost being question choosin...

The Fractal Dimension (FD) of an image defines the roughness using a real number which is highly associated with the human perception of surface roughness. It has been applied successfully for many computer vision applications such as texture analysis, segmentation and classification. Several techniques can be found in literature to estimate FD. One such technique is Differential Box Counting (...

The fractal dimension Df has been widely used to describe the structural and morphological characteristics of aggregates. Box-counting (BC) power law (PL) are most common methods calculate However, prefactor k, as another important property, received less attention. Furthermore, there is no relevant research about BC (kBC). This work applied a tunable aggregation model generate series three-dim...