DocumentCode :
2962847
Title :
Recurrent Clifford Support Machines
Author :
Bayro-Corrochano, Eduardo ; Vallejo-Gutierrez, J. Refugio ; Arana-Daniel, Nancy
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci. Dept., CINVESTAV Centro de Investig. y de Estudios Av., Zapopan
fYear :
2008
fDate :
1-8 June 2008
Firstpage :
3613
Lastpage :
3618
Abstract :
This paper introduces the recurrent Clifford support vector machines (RCSVM). First we explain the generalization of the real- and complex-valued support vector machines using the Clifford geometric algebra. In this framework we handle the design of kernels involving the Clifford or geometric product and one redefines the optimization variables as multivectors. This allows us to have a multivector as output therefore we can represent multiple classes according to the dimension of the geometric algebra in which we work. We show that one can apply CSVM to build a recurrent CSVM.We study the performance of the recurrent CSVM with experiments using time series and tasks of visually guided robotics.
Keywords :
algebra; geometry; support vector machines; Clifford geometric algebra; complex-valued support vector machines; real-valued support vector machines; recurrent Clifford support vector machines; Algebra; Design optimization; Equations; Kernel; Robots; Support vector machine classification; Support vector machines;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 2008. IJCNN 2008. (IEEE World Congress on Computational Intelligence). IEEE International Joint Conference on
Conference_Location :
Hong Kong
ISSN :
1098-7576
Print_ISBN :
978-1-4244-1820-6
Electronic_ISBN :
1098-7576
Type :
conf
DOI :
10.1109/IJCNN.2008.4634315
Filename :
4634315
Link To Document :
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