13 October 2008 Computer-simulated development process of Chinese characters font cognition
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Proceedings Volume 7127, Seventh International Symposium on Instrumentation and Control Technology: Sensors and Instruments, Computer Simulation, and Artificial Intelligence; 71272D (2008); doi: 10.1117/12.806738
Event: Seventh International Symposium on Instrumentation and Control Technology, 2008, Beijing, China
Abstract
The research of Chinese characters cognition is an important research aspect of cognitive science and computer science, especially artificial intelligence. In this paper, according as the traits of Chinese characters the database of Chinese characters font representations and the model of computer simulation of Chinese characters font cognition are constructed from the aspect of cognitive science. The font cognition of Chinese characters is actual a gradual process and there is the accumulation of knowledge. Through using the method of computer simulation, the development model of Chinese characters cognition was constructed. And this is the important research content of Chinese characters cognition. This model is based on self-organizing neural network and adaptive resonance theory (ART) neural network. By Combining the SOFM and ART2 network, two sets of input were trained. Through training and testing methods, the development process of Chinese characters cognition based on Chinese characters cognition was simulated. Then the results from this model and could be compared with the results that were obtained only using SOFM. By analyzing the results, this simulation suggests that the model is able to account for some empirical results. So, the model can simulate the development process of Chinese characters cognition in a way.
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Jing Chen, Zhichun Mu, Dehui Sun, Dunli Hu, "Computer-simulated development process of Chinese characters font cognition", Proc. SPIE 7127, Seventh International Symposium on Instrumentation and Control Technology: Sensors and Instruments, Computer Simulation, and Artificial Intelligence, 71272D (13 October 2008); doi: 10.1117/12.806738; https://doi.org/10.1117/12.806738
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KEYWORDS
Cognition

Cognitive modeling

Neural networks

Computer simulations

Data modeling

Artificial intelligence

Evolutionary algorithms

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