Abstract
This paper 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.
Original language | English |
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Pages (from-to) | 2273-2283 |
Number of pages | 11 |
Journal | IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics |
Volume | 34 |
Issue number | 6 |
DOIs | |
Publication status | Published - 1 Dec 2004 |
Keywords
- Digit and command interpretation
- Electronic book
- Genetic algorithm
- Neural networks
ASJC Scopus subject areas
- Control and Systems Engineering
- Software
- General Medicine
- Information Systems
- Human-Computer Interaction
- Computer Science Applications
- Electrical and Electronic Engineering