Accepted

Articles recently accepted for publication:

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Random walks on random networks of cliques: Inferring the network structure

A Nannini and D H Zanette

We study the properties of discrete-time random walks on networks formed by randomly interconnected cliques, namely, random networks of cliques. Our purpose is to derive the parameters that define the network structure –specifically, the distribution of clique size and the abundance of inter-clique links– from the observation of selected statistical features along the random walk. To this end, we apply a Bayesian approach based on recording the times spent by the walker inside successively visited cliques. The procedure is illustrated with some numerical examples of diverse complexity, where the relevant structural parameters are successfully recovered.

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Wavelet q-extropies of fractal signals

Julio César Ramı́rez Pacheco, Joel Antonio Trejo Sánchez, Luis Rizo Domı́nguez

The standard Tsallis and Rényi extropies of parameter q are extended to the time-scale domain and closed-form expressions of these extropies for fractal signals of parameter α are obtained. Wavelet extropy planes are computed for a range of the fractality parameter α and signal length N which allows to unveil the properties and potential applications of wavelet q-extropies on fractals. Results indicate that wavelet q-extropies allow to accurately describe the complexities of fractals since they are maximum for completely random samples, decreasing for correlated fractals and increasing for uncorrelated fractals. Unlike Shannon and Rényi, Tsallis extropies display a constant region, symmetric on α, and which allows to classify fractals based on a simple heuristic of wavelet extropy values. Finally, the application of wavelet Tsallis extropies allows to differentiate electroencephalogram (EEG) times series from volunteers with eyes closed and eyes open.

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