Title :
The Research of Alphabet Identification Based on Genetic BP Neural Network
Author :
Liu, Lina ; Qi, Huijuan ; Liu, Jia
Author_Institution :
Shijiazhuang Inst. of Railway Technol., Shijiazhuang, China
Abstract :
The Back Propagation (BP) neural network genetic algorithm was used to identify alphabet, and the new algorithm combine the advantages of both genetic algorithm and the BP neural network. Genetic learning algorithm was used for the global optimization and BP training algorithm to accurately optimize the neural network weights and training the neural network to learn letter recognition algorithm. Add-noise alphabet of MATLAB simulation results show that the new network error recognition rate reduced by 10% compared to BP neural network and the recognition speed is also faster than the traditional BP neural network with accuracy and fast convergence.
Keywords :
backpropagation; character recognition; genetic algorithms; neural nets; BP training algorithm; MATLAB simulation; add-noise alphabet; alphabet identification; back propagation neural network genetic algorithm; genetic BP neural network; genetic learning algorithm; global optimization; letter recognition algorithm; network error recognition rate; neural network weights; recognition speed; Algorithm design and analysis; Biological neural networks; Genetic algorithms; Genetics; Noise; Training; BP neural network; additive noise; alphabet identification; genetic algorithm;
Conference_Titel :
Intelligent Human-Machine Systems and Cybernetics (IHMSC), 2012 4th International Conference on
Conference_Location :
Nanchang, Jiangxi
Print_ISBN :
978-1-4673-1902-7
DOI :
10.1109/IHMSC.2012.12