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The application of Tikhonov's regularization method [Tikhonov & Arsenin (1977). Solution of Ill-Posed Problems. New York: Wiley] for the solution of illposed problems in small-angle-scattering-data treatment is considered. Simple regularization algorithms are proposed for solving convolution equations in data desmearing (slit-width and polychromaticity problems) as well as for polydispersity problems. A general indirect approach of data processing based on the regularization method is described. Comparison with other data-treatment methods is made.

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Polyaniline (PANI) based memristive devices have emerged as promising candidates for hardware implementation of artificial synapses (the key components of neuromorphic systems) due to their high flexibility, low cost, solution processability, three-dimensional stacking capability, and biocompatibility. Here, we report on a way of the significant improvement of the switching rate and endurance of PANI-based memristive devices. The reduction of the PANI active channel dimension leads to the increase in the resistive switching rate by hundreds of times in comparison with the conventional one. The miniaturized memristive device was shown to be stable within at least 104 cyclic switching events between high- and low-conductive states with a retention time of at least 103 s. The obtained results make PANI-based memristive devices potentially widely applicable in neuromorphic systems.