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- W2378621326 abstract "Aiming at the problem of local minimum,slow convergence of the BP neural network,the learning algorithm based on particle swarm optimization is designed and analyzed,which is applied to image restoration.Firstly,noiseless images are processed by Gaussian noise.Then,the result image and the noiseless images are made training pair,which is used in training the optimized BP neural network.Lastly,use the BP neural network to restore test images for the purpose of removing noise.The simulation results show that the effect of PSO-BP algorithm to recover the image have fast convergence rate and less iterations,is better than the BP neural network both in Normalized Mean Square Error( NMSE) and the Peak Signal to Noise Ratio( PSNR)." @default.
- W2378621326 created "2016-06-24" @default.
- W2378621326 creator A5053350756 @default.
- W2378621326 date "2014-01-01" @default.
- W2378621326 modified "2023-09-23" @default.
- W2378621326 title "A Method of Image Restoration Based on Particle Swarm Optimization for BP Neural Network" @default.
- W2378621326 hasPublicationYear "2014" @default.
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