Title :
A New Method of Image Compression Based on Quantum Neural Network
Author :
Li Huifang ; Li Mo
Author_Institution :
Sch. of Electron. Inf., Northwestern Polytech. Univ., Xian, China
Abstract :
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.
Keywords :
backpropagation; genetic algorithms; image coding; image reconstruction; neural nets; quantum gates; genetic algorithm; image compression method; image reconstruction; quantum computing neuron model; quantum gates; quantum neural network; three layer quantum back propagation network model; Artificial neural networks; Image coding; Image reconstruction; Logic gates; Neurons; Quantum computing; Training; Genetic Algorithm; Image Compression; Mutational Clamping; Quantum Neural Networks;
Conference_Titel :
Information Science and Management Engineering (ISME), 2010 International Conference of
Conference_Location :
Xi´an
Print_ISBN :
978-1-4244-7669-5
Electronic_ISBN :
978-1-4244-7670-1
DOI :
10.1109/ISME.2010.242