Fractal curves were generated on square initiators and rated in terms of complexity by eight viewers. The stimuli differed in fractional dimension, recursion, and number of segments in their generators. Across six stimulus sets, recursion accounted for most of the variance in complexity judgments, but among stimuli with the most recursive depth, fractal dimension was a respectable predictor. Si...

This paper introduces a method for modification of the formula of the fractal box counting dimension. The method is based on the utilization of the probability distribution formula in the fractal box count. The purpose of this method is to use it for the discrimination of oil spill areas from the surrounding features e.g., sea surface and look-alikes in RADARSAT-1 SAR data. The result shows tha...

The presence of correlated randomness in EEG time series signal buried in random noise was analyzed with the Higuchi fractal algorithm. The signal recognition algorithm design was built on the fact that the theoretical fractal dimension value of 2 is an indicator for a white noise time series and correlated randomness would alter the fractal dimension value from 2. However, the limited number o...

We show that renormalization group (RG) theory applied to complex networks are useful to classify network topologies into universality classes in the space of configurations. The RG flow readily identifies a small-world/fractal transition by finding a trivial stable fixed point of a complete graph, and two unstable fixed points consisting of (i) a pure fractal topology and (ii) a fractal with s...

We show that renormalization group (RG) theory applied to complex networks is useful to classify network topologies into universality classes in the space of configurations. The RG flow readily identifies a small-world-fractal transition by finding (i) a trivial stable fixed point of a complete graph, (ii) a nontrivial point of a pure fractal topology that is stable or unstable according to the...

This paper presents a multi-fractal based approach for the classification of emphysema patterns by calculating the local singularity coefficients of an image using different intensity measures. One of the primary statistical measures of self-similarity used in the processing of tissue images is holder exponent (αvalue) that represents the power law which the intensity distribution satisfies in ...