Image Restoration Algorithm for Reliable Block Quantum Cellular Automata Gate
نویسنده
چکیده
The fault-tolerance properties of the classical Quantum Cellular Automata (QCA) Majority gate, as well as the AND-gate, suffer from precision errors in inherent in manufacturing on a nanometer scale. Due to these implementation problems, a new approach for QCA was developed. A solution using multiple QCA cells in block configuration is an improvement but will may not work depending on the number and pattern of cells that are out of alignment. Image segmentation and restoration algorithms have been previously used successfully in manufacturing automation to correct or compensate for errors in fabrication. This proposal investigates and draws out the mathematical model and approach to apply a neural network-based image restoration algorithm to the QCA block Majority gate, as well as the AND-gate, to produce greater reliability. Study of effectiveness is presented.
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