Journal of Jilin University(Information Science Ed ›› 2016, Vol. 34 ›› Issue (1): 147-151.

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Hologram Compression Using BP Neural Network by Modified Particle Swarm Optimization

WANG Ganggang, LIAO Qing, XU Yurui, LIU Le, HOU Alin   

  1. College of Computer Science and Engineering, Changchun University of Technology, Changchun 130012, China
  • Received:2014-12-01 Online:2016-01-25 Published:2016-05-10

Abstract:

To solve the problem that hologram contains a large amount of data and performance of reproduced hologram is not ideal. A method is proposed to adjust dynamically learning factor and inertia weight for the PSO (Particle Swarm Optimization). The MPSO-BP(Modified Particle Swarm Optimizing BP Neural Network) is constructed combining the modified algorithm with BP(Back Propagation) neural network. Comparing with the BP neural network compression and PSO-BP(Particle Swarm Optimizing BP Neural Network) compression, the network has the advantages of better performance of reproducing hologram while maintaining a good compression efficiency.

Key words: particle swarm optimization ( PSO) algorithm, modified particle swarm optimizing(MPSO-BP) neural network, hologram

CLC Number: 

  • TP391