MARKOV SPECTRA OF SELF-SIMILAR NETWORKS BY SUBSTITUTION RULE

For a class of self-similar networks generated by substitution rules, we investigate them in terms of normalized Laplacian spectra. Accordingly, we obtain the recurrent structure of Markov spectra for these self-similar networks, and also estimate the smallest positive eigenvalue for Laplace operator.

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