Application study on neural network and genetic algorithm in the interpretation of correlation peak
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Department of Optical and Electronic Engineering, Ordnance Engineering College, Shijiazhuang 050003, China
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Corresponding author:
SHAO Jun, sj_opt@163.com
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Received Date:
2008-06-12
Accepted Date:
2008-08-27
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Abstract
In order to identify correlation peak better in the research of target recognition technology based on coherent optics,combining the genetic algorithm(GA)and the artificial neural network(ANN),based on GA and back propagation(BP)neural network,a correlation peak identification system was built with GA optimizing the initial weights and thresholds of the ANN.The optimized identification system could not only avoid the tendency of local minimum and slow convergence speed in ANN training,but also overcome the shortage of local precise searching capacity in GA.It realizes the superiority complementation between the both the methods,and is helpful to solve the problem of recognizing correlation peak.The testing results show that the improved method makes full use of the advantages of GA and BP algorithm,and gets much better interpretation effect.
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