An Image Compression Algorithm Combining Genetic with BP Neural Network Algorithm

To compensate the defects of LM(Levenberg-Marquardt)algorithm,an hybrid learning algorithm(GA-LMbp)in which improved genetic algorithm and LM algorithm were proposed and were used to optimizing the neural network.Firstly,the algorithm retained a set of global optimal approximate solution(initial weights and threshold values of BP network) through being improved genetic algorithm. Then,BP network were optimized by LM algorithm with the approximate solution as initial values,and the BP network were used for image compression. The experimental results showed that the new algorithm improves the learning ability and convergence speed of the network,and it succeeds in avoiding LMbp sinking into flat area or local minimum value.