DocumentCode :
1797919
Title :
Gain parameters based complex-valued backpropagation algorithm for learning and recognizing hand gestures
Author :
Yuanshan Liu ; He Huang ; Tingwen Huang
Author_Institution :
Sch. of Electron. & Inf. Eng., Soochow Univ., Suzhou, China
fYear :
2014
fDate :
6-11 July 2014
Firstpage :
2162
Lastpage :
2166
Abstract :
In this paper, an improved complex-valued backpropagation algorithm with gain parameters is proposed. It is then employed to train a complex-valued feedforward neural network with one hidden layer. The well-trained complex-valued neural network is finally applied to deal with the recognition problem of 26 hand gestures. The results of experiment clearly show that much better performance can be achieved by our improved complex-valued backpropagation algorithm than some existing methods.
Keywords :
backpropagation; feedforward neural nets; gesture recognition; complex-valued backpropagation algorithm; feedforward neural network; gain parameters; hand gesture recognition; learning; Backpropagation; Backpropagation algorithms; Biological neural networks; Convergence; Joints; Neurons;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks (IJCNN), 2014 International Joint Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4799-6627-1
Type :
conf
DOI :
10.1109/IJCNN.2014.6889685
Filename :
6889685
Link To Document :
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