Nonlinear resistive grids have been extensively used in the past for achieving image filtering, focused on both smoothing and edge detection, by resorting to the nonlinear constitutive branch relationships of the elements in the array in order to carry out in fact a minimization algorithm. In this chapter, a specially tailored fully analytical charge-controlled memristor model is introduced and used in a memristive grid in order to handle the edge detection. The performance of the grid has been tested on a set of 500 images (clean and noisy) and shows an excellent agreement with the outcomes produced by humans.
Part of the book: Advances in Memristor Neural Networks