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A New Method of Image Compression Based on Quantum Neural Network

机译:一种基于量子神经网络的图像压缩方法

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In this paper we combine with quantum neural networks and image compression using Quantum Gates as the basic unit of quantum computing neuron model, and establish a three layer Quantum Back Propagation Network model, then the model is used for realizing image compression and reconstruction. Since the initial weights of neural networks were slow convergence, we use Genetic Algorithm (GA) to optimize the neural network weights, and present a mechanism called clamping to improve the genetic algorithm. Finally, we combined the Genetic Algorithm with quantum neural networks to finish image compression. Through an experiment we can see the superiority of the improved algorithm.
机译:在本文中,我们将量子神经网络和图像压缩组合使用量子门作为量子计算神经元模型的基本单元,并建立三层量子背部传播网络模型,然后模型用于实现图像压缩和重建。由于神经网络的初始重量是缓慢的收敛性,我们使用遗传算法(GA)来优化神经网络权重,并且呈现称为钳位的机制以提高遗传算法。最后,我们将遗传算法与量子神经网络结合完成以完成图像压缩。通过实验,我们可以看到改进算法的优越性。

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