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