作　　者： ; ; ; ;

机构地区： 深圳大学信息工程学院

出　　处： 《深圳大学学报（理工版）》 2008年第2期153-157,共5页

摘　　要： 基于传统反向传播(back propagation,BP)网络,提出一种结合细菌觅食算法(bacterial fora-ging algorithm,BFA)的改进型BP网络(BFA-BP),并将其用于图像压缩.为克服传统BP网络容易陷入局部极小值的缺点,算法引入BFA特有的复制和驱散操作,以提高网络收敛速度,加强全局寻优能力.对标准测试图像进行仿真实验表明,该算法能有效提高重建图像质量. An improved back propagation network （ BP network） combined with bacterial foraging algorithm （BFA） was applied to image compression. The particular operations, i.e., reproduction and elimination-dispersal in BFA, were introduced to the BFA-BP algorithm to prevent the premature saturation in traditional BP network. The convergence speed and global search ability are enhanced. The BFA-BP algorithm was evaluated on standard test images in comparison with traditional BP algorithm. The simulation results demonstrate the effectiveness of the proposed algorithm in improving the quality of reconstructed images.

关 键 词： 人工神经网络 反向传播 细菌觅食算法 生物启发式计算 图像压缩

领　　域： [电子电信] [电子电信] [自动化与计算机技术] [自动化与计算机技术]