DocumentCode :
2325119
Title :
Real-time PCA (principal component analysis) implementation on DSP
Author :
Han, Dongho ; Rao, Yadunandana N. ; Principe, Jose C. ; Gugel, Karl
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Florida, Gainesville, FL, USA
Volume :
3
fYear :
2004
fDate :
25-29 July 2004
Firstpage :
2159
Abstract :
PCA (principal component analysis) is a wellknown statistical technique used in many signal processing applications. An on-line temporal PCA learning algorithm is implemented on a floating-point DSP for real-time applications. This algorithm is coded in assembly language to optimize. The experimental results showed that the implemented on-line temporal PCA algorithm not only can accurately estimate the principal components from the input but also can track the principal components from the time varying input. And this algorithm can be applied in space easily by using spacial signals as its inputs instead of using the past inputs as in temporal PCA.
Keywords :
assembly language; digital signal processing chips; floating point arithmetic; optimisation; principal component analysis; assembly language; digital signal processor; floating point DSP; learning algorithm; online temporal PCA algorithm; optimization; principal component analysis; principal component estimation; real time applications; spacial signals; statistical technique; time varying input; tracking; Application software; Convergence; Covariance matrix; Delay lines; Digital signal processing; Digital signal processing chips; Neural engineering; Principal component analysis; Signal processing algorithms; Symmetric matrices;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 2004. Proceedings. 2004 IEEE International Joint Conference on
ISSN :
1098-7576
Print_ISBN :
0-7803-8359-1
Type :
conf
DOI :
10.1109/IJCNN.2004.1380953
Filename :
1380953
Link To Document :
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