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Digit and command interpretation for electronic book using neural network and genetic algorithm

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2 Author(s)
Lam, H.K. ; Dept. of Electron. & Inf. Eng., Hong Kong Polytech. Univ., China ; Leung, F.H.F.

This work presents the interpretation of digits and commands using a modified neural network and the genetic algorithm. The modified neural network exhibits a node-to-node relationship which enhances its learning and generalization abilities. A digit-and-command interpreter constructed by the modified neural networks is proposed to recognize handwritten digits and commands. A genetic algorithm is employed to train the parameters of the modified neural networks of the digit-and-command interpreter. The proposed digit-and-command interpreter is successfully realized in an electronic book. Simulation and experimental results will be presented to show the applicability and merits of the proposed approach.

Published in:

Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on  (Volume:34 ,  Issue: 6 )

Date of Publication:

Dec. 2004

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