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Charge-Controlled Memristor Grid for Edge Detection

In: Advances in Memristor Neural Networks - Modeling and Applications

Author

Listed:
  • Arturo Sarmiento Reyes
  • Yojanes R. Velasquez

Abstract

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.

Suggested Citation

  • Arturo Sarmiento Reyes & Yojanes R. Velasquez, 2018. "Charge-Controlled Memristor Grid for Edge Detection," Chapters, in: Calin Ciufudean (ed.), Advances in Memristor Neural Networks - Modeling and Applications, IntechOpen.
    • Handle: RePEc:ito:pchaps:151786
    DOI: 10.5772/intechopen.78610
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    More about this item

    Keywords

    memristor modeling; memristive grids; symbolic memristor modeling; edge-detection; image processing;
    All these keywords.

    JEL classification:

    • C60 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - General

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