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A Novel Functional Sized Population Quantum Evolutionary Algorithm for Fractal Image Compression

机译:一种用于分形图像压缩的新型功能大小群体量子进化算法

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Quantum Evolutionary Algorithm (QEA) is a novel optimization algorithm which uses a probabilistic representation for solution and is highly suitable for combinatorial problems like Knapsack problem. Fractal image compression is a well-known problem which is in the class of NP-Hard problems. Genetic algorithms are widely used for fractal image compression problems, but QEA is not used for this kind of problems yet. This paper uses a novel Functional Sized population Quantum Evolutionary Algorithm for fractal image compression. Experimental results show that the proposed algorithm has a better performance than GA and conventional fractal image compression algorithms.
机译:量子进化算法(QEA)是一种新颖的优化算法,其利用概率表示解决方案,非常适合作为背包问题等组合问题。分形图像压缩是一个众所周知的问题,它是NP难题的类别。遗传算法广泛用于分形图像压缩问题,但QEA尚未用于这种问题。本文采用了一种新型功能大小的群体量子进化算法,用于分形图像压缩。实验结果表明,该算法具有比GA和传统分形图像压缩算法更好的性能。

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