DocumentCode :
3222874
Title :
The design of digit recognition teaching experiment based on PCA and BP neural network
Author :
Panpan Liu ; Jianyi Guo ; Zhengtao Yu ; Huafeng Li ; Yantuan Xian
Author_Institution :
Sch. of Inf. Eng. & Autom., Kunming Univ. of Sci. & Technol., Kunming, China
fYear :
2015
fDate :
23-25 May 2015
Firstpage :
4132
Lastpage :
4135
Abstract :
In order to resolve the comprehension difficulties of theory and implementation about multi-objective decision in "Decision Analysis and Decision Support" course for postgraduates, digit recognition experiment is introduced into teaching practice. PCA method is used in the process of digit recognition, which is one of multi-objective decision methods. The digital recognition principles are firstly described based on PCA and BP neural network. Then, a teaching experimental scheme is given, and the algorithm\´s design and simulation can be carried in MATLAB. So that students can deeply understand and master the theoretical knowledge through the open experiment. It has been found that the experiment can effectively improve the students\´ practical ability and the understanding of the process of multi-objective decision.
Keywords :
backpropagation; character recognition; computer aided instruction; educational courses; neural nets; principal component analysis; teaching; BP neural network; PCA; decision analysis and decision support course; digit recognition teaching experiment design; multiobjective decision methods; Algorithm design and analysis; Classification algorithms; Feature extraction; Neural networks; Principal component analysis; Training; BP neural network; Data analysis; MATLAB; Multi-objective; PCA;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control and Decision Conference (CCDC), 2015 27th Chinese
Conference_Location :
Qingdao
Print_ISBN :
978-1-4799-7016-2
Type :
conf
DOI :
10.1109/CCDC.2015.7162656
Filename :
7162656
Link To Document :
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